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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.2025.1508774</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>Association between hyperuricemia and dietary retinol intake in Southwest China: a cross-sectional study based on CHNS database</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Liang</surname> <given-names>Yi</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/572506/overview"/>
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</contrib>
<contrib contrib-type="author">
<name><surname>Qiao</surname> <given-names>Tian</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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</contrib>
<contrib contrib-type="author">
<name><surname>Ni</surname> <given-names>Xiaorong</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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</contrib>
<contrib contrib-type="author">
<name><surname>Yang</surname> <given-names>Lihui</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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</contrib>
<contrib contrib-type="author">
<name><surname>Yao</surname> <given-names>Tianhua</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name><surname>Liu</surname> <given-names>Yiya</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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<aff id="aff1"><sup>1</sup><institution>Department of Clinical Nutrition, Affiliated Hospital of Guizhou Medical University</institution>, <addr-line>Guiyang</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University</institution>, <addr-line>Guiyang</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>Guizhou Center for Disease Control and Prevention</institution>, <addr-line>Guiyang</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0001">
<p>Edited by: Thomas Wilson, Aberystwyth University, United Kingdom</p>
</fn>
<fn fn-type="edited-by" id="fn0002">
<p>Reviewed by: Hongrui Li, University of North Carolina at Chapel Hill, United States</p>
<p>Jia Peng, University of Kentucky, United States</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Yiya Liu, <email>liuyiya163@163.com</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>22</day>
<month>01</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>12</volume>
<elocation-id>1508774</elocation-id>
<history>
<date date-type="received">
<day>09</day>
<month>10</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>03</day>
<month>01</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2025 Liang, Qiao, Ni, Yang, Yao and Liu.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Liang, Qiao, Ni, Yang, Yao and Liu</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>Hyperuricemia is increasingly common in Southwestern China and poses significant health risks, including gout and cardiovascular disease. Retinol intake has been hypothesized to affect uric acid levels, but this relationship remains unclear.</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>Data from 4,658 participants in the China Health and Nutrition Survey (CHNS) from 1991 to 2018 were analyzed. Dietary retinol intake was categorized using quantile-based methods, and hyperuricemia was identified as the primary outcome. Logistic regression models were used to estimate odds ratios and 95% confidence intervals, with analyses stratified by gender. Restricted cubic splines were utilized to evaluate the dose&#x2013;response relationship.</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>The average age of participants was 40&#x202F;&#x00B1;&#x202F;17.83&#x202F;years, and 20.29% met the criteria for hyperuricemia. Logistic regression analysis identified a positive association between dietary retinol intake and hyperuricemia, with a more pronounced effect observed in men. The restricted cubic spline analysis revealed that the odds of hyperuricemia increased significantly when dietary retinol intake exceeded 3,538&#x202F;IU/day for men and 4,504&#x202F;IU/day for women.</p>
</sec>
<sec id="sec4">
<title>Conclusion</title>
<p>High dietary retinol intake is associated with an increased risk of hyperuricemia, with a stronger association observed in males. These findings suggest that dietary retinol intake under recommendation levels might be necessary to prevent hyperuricemia-related adverse health outcomes.</p>
</sec>
</abstract>
<kwd-group>
<kwd>hyperuricemia</kwd>
<kwd>dietary retinol</kwd>
<kwd>cross-sectional design</kwd>
<kwd>CHNS</kwd>
<kwd>dose&#x2013;response</kwd>
</kwd-group>
<contract-sponsor id="cn1">National Natural Science Foundation of China<named-content content-type="fundref-id">10.13039/501100001809</named-content></contract-sponsor>
<contract-sponsor id="cn2">Guizhou Medical University<named-content content-type="fundref-id">10.13039/501100010265</named-content></contract-sponsor>
<counts>
<fig-count count="1"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="52"/>
<page-count count="7"/>
<word-count count="5639"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Nutritional Epidemiology</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec5">
<label>1</label>
<title>Introduction</title>
<p>Hyperuricemia, characterized by elevated serum uric acid levels, arises due to urate overproduction or its impaired excretion through the kidneys and gastrointestinal tract (<xref ref-type="bibr" rid="ref1">1</xref>). The prevalence of hyperuricemia varies widely across populations, ranging from 8.9 to 24.4% (<xref ref-type="bibr" rid="ref2 ref3 ref4 ref5">2&#x2013;5</xref>). It serves as a major risk factor for gout (<xref ref-type="bibr" rid="ref6">6</xref>) and is independently associated with chronic conditions, including type 2 diabetes (<xref ref-type="bibr" rid="ref7">7</xref>), hypertension (<xref ref-type="bibr" rid="ref8">8</xref>), metabolic syndrome (<xref ref-type="bibr" rid="ref9">9</xref>), and chronic kidney disease (<xref ref-type="bibr" rid="ref10">10</xref>). Various factors contribute to the onset of hyperuricemia, in addition to genetic predisposition and environmental influences, dietary habits like excessive alcohol consumption (<xref ref-type="bibr" rid="ref11">11</xref>), high-purine diets (<xref ref-type="bibr" rid="ref12">12</xref>), and the intake of high-fructose or sugary beverages (<xref ref-type="bibr" rid="ref13">13</xref>) are well-established contributors to elevated serum uric acid levels. Additionally, previous studies have suggested potential associations between hyperuricemia and the intake levels of various vitamins, including vitamins C, D, E, and B1 (<xref ref-type="bibr" rid="ref1">1</xref>, <xref ref-type="bibr" rid="ref14 ref15 ref16">14&#x2013;16</xref>).</p>
<p>Retinol is an effective exogenous antioxidant and is believed to be involved in uric acid metabolism (<xref ref-type="bibr" rid="ref17">17</xref>). Several studies have observed a positive correlation between serum retinol and uric acid levels (<xref ref-type="bibr" rid="ref18 ref19 ref20">18&#x2013;20</xref>), suggesting that higher retinol intake might elevate the risk of hyperuricemia. However, findings from retinol intake studies have been inconsistent. For instance, a study in Korea found lower dietary retinol intake in hyperuricemic individuals compared to controls (<xref ref-type="bibr" rid="ref21">21</xref>), while a comparative study involving Australian and Norwegian cohorts reported a positive correlation between retinol intake and uric acid levels only in the Australian cohort (<xref ref-type="bibr" rid="ref22">22</xref>). Furthermore, a cross-sectional survey in Taiwan found no significant association between retinol intake and hyperuricemia (<xref ref-type="bibr" rid="ref23">23</xref>). These inconsistencies might be attributed to population-specific genetic variations in vitamin A metabolism (<xref ref-type="bibr" rid="ref24">24</xref>), differences in overall dietary patterns affecting nutrient interactions (<xref ref-type="bibr" rid="ref25">25</xref>), and varying environmental factors that influence vitamin bioavailability (<xref ref-type="bibr" rid="ref26">26</xref>, <xref ref-type="bibr" rid="ref27">27</xref>). Such variations highlight the importance of population-specific investigations to better understand the relationship between retinol intake and hyperuricemia.</p>
<p>Given these inconsistent and limited findings on the relationship between dietary retinol intake and hyperuricemia, further research is warranted. This study aims to evaluate the relationship between dietary retinol intake and the risk of hyperuricemia in the population of Southwest China, using data from the China Health and Nutrition Survey (CHNS).</p>
</sec>
<sec sec-type="methods" id="sec6">
<label>2</label>
<title>Methods</title>
<sec id="sec7">
<label>2.1</label>
<title>Study participants</title>
<p>The CHNS is an ongoing open-cohort longitudinal survey that has completed 10 rounds of data collection between 1989 and 2018. The survey employed a multi-stage random cluster sampling method across nine provinces in China, representing various levels of socioeconomic development. Each province was divided into counties and cities based on income levels (low, middle, and high), and a weighted sampling method was employed to randomly select four counties and two cities. Within the counties, villages and townships were randomly selected, while urban and suburban neighborhoods within the cities were also chosen at random. Finally, 20 households were randomly selected from each village, town, or community, and all household members participated in the CHNS interview. This survey aims to comprehensively capture key public health risk factors and health outcomes at the individual, household, and community levels, along with demographic, social, and economic variables. Since 2009, the CHNS has also collected geospatial coordinates of all respondents and key community resources, fasting blood samples from participants aged seven and above, and toenail samples from those aged two and above. Details have been described elsewhere (<xref ref-type="bibr" rid="ref28">28</xref>). From 1991 to 2018, a total of 18,713 individuals participated in the survey, with 16,673 being adults aged 18 and above. For this study, we concentrated on 4,658 participants from Guizhou province who supplied detailed baseline information, completed dietary surveys, and provided blood samples.</p>
<p>The CHNS was approved by the institutional review boards of the University of North Carolina at Chapel Hill and the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention. Written informed consent was obtained from all participants prior to data collection.</p>
</sec>
<sec id="sec8">
<label>2.2</label>
<title>Dietary assessment</title>
<p>Dietary data were collected using a three-day 24-h recall method, combined with a food inventory method. Household food consumption was determined by examining the inventory changes from start to finish each day, using weighing and measuring techniques to ensure data accuracy. For foods that could not be directly weighed, estimates of wasted weight were used to compensate for missing data. A kitchen scale with a precision of grams was used for weighing food to ensure accurate measurements. Participants were thoroughly questioned about all food consumed in the past 24&#x202F;h, whether eaten at home or away. The weight of individual food consumption was estimated using the household inventory method to calculate the total amount of each dish, multiplied by the individual&#x2019;s reported consumption proportion, and further estimates of salt and oil intake were made. To exclude outliers, extreme dietary data were filtered based on the assessor&#x2019;s professional judgment. The three-day recall method combined with the food inventory method used in this study showed a high correlation across food categories (<xref ref-type="bibr" rid="ref29">29</xref>), enhancing the accuracy of dietary recall data. Energy and nutrient intake were calculated using the Chinese Food Composition Table (<xref ref-type="bibr" rid="ref30">30</xref>).</p>
</sec>
<sec id="sec9">
<label>2.3</label>
<title>Measurement of serum uric acid</title>
<p>Serum uric acid levels were measured using an enzymatic colorimetric method on a Hitachi 7,600 automated analyzer (Hitachi, Tokyo, Japan) with reagents from Randox Laboratories (Crumlin, United Kingdom). Hyperuricemia was defined as serum uric acid levels of &#x2265;7&#x202F;mg/dL in men and&#x202F;&#x2265;&#x202F;6&#x202F;mg/dL in women (<xref ref-type="bibr" rid="ref31">31</xref>). Details on fasting blood sample collection have been described previously (<xref ref-type="bibr" rid="ref32">32</xref>).</p>
</sec>
<sec id="sec10">
<label>2.4</label>
<title>Covariates</title>
<p>Smoking was defined as the consumption of at least one cigarette per day. Alcohol consumption was assessed by asking participants if they had consumed beer or other alcoholic beverages in the past year, and responses were categorized as either &#x2018;Yes&#x2019; or &#x2018;No.&#x2019; Physical activity was measured across several domains: occupational (light, moderate, and vigorous), household (e.g., food preparation, shopping, laundry, child care), transportation (e.g., driving, walking, cycling), and leisure (e.g., yoga, dancing). Participants reported the average hours spent per week on these activities over the past year. Height and weight were measured according to World Health Organization (WHO) standards, with weight recorded to the nearest 0.01&#x202F;kg and height to the nearest 0.1&#x202F;cm. BMI was categorized into four groups: underweight (BMI&#x202F;&#x003C;&#x202F;18.5&#x202F;kg/m<sup>2</sup>), normal weight (BMI 18.5&#x2013;23.9&#x202F;kg/m<sup>2</sup>), overweight (BMI 24.0&#x2013;27.9&#x202F;kg/m<sup>2</sup>), and obesity (BMI&#x202F;&#x2265;&#x202F;28.0&#x202F;kg/m<sup>2</sup>) (<xref ref-type="bibr" rid="ref33">33</xref>). Blood pressure was measured three times using a mercury sphygmomanometer, and the average reading was recorded. Hypertension was defined as an average systolic pressure&#x202F;&#x2265;&#x202F;140&#x202F;mmHg, diastolic pressure&#x202F;&#x2265;&#x202F;90&#x202F;mmHg, self-reported hypertension, or current use of antihypertensive medication (<xref ref-type="bibr" rid="ref34">34</xref>). Type 2 diabetes was defined as a fasting blood glucose level&#x202F;&#x2265;&#x202F;7&#x202F;mmol/L or an HbA1c level&#x202F;&#x2265;&#x202F;6.5% (<xref ref-type="bibr" rid="ref35">35</xref>).</p>
</sec>
<sec id="sec11">
<label>2.5</label>
<title>Statistical analysis</title>
<p>We analyzed the distribution of sociodemographic characteristics, disease conditions, and dietary intake across quintiles of retinol consumption. Continuous variables were expressed as mean&#x202F;&#x00B1;&#x202F;standard deviation and categorical variables were presented as frequencies and percentages. Logistic regression models were employed to assess the association between daily retinol intake and hyperuricemia. Models were adjusted for potential confounders, including age, sex, BMI, alcohol consumption, smoking status, physical activity, and comorbid conditions such as hypertension, diabetes, and chronic kidney disease. Odds ratios (ORs) and 95% confidence intervals (CIs) were reported. Subgroup analyses were performed to explore the potential effect modification by sex. Restricted cubic spline analysis was used to evaluate the dose&#x2013;response relationship between dietary retinol intake and hyperuricemia. All tests were two-tailed, and <italic>p</italic>&#x202F;&#x003C;&#x202F;0.05 were considered statistically significant.</p>
</sec>
</sec>
<sec sec-type="results" id="sec12">
<label>3</label>
<title>Results</title>
<sec id="sec13">
<label>3.1</label>
<title>Participant characteristics</title>
<p>The study included 4,658 participants with an average age of 40&#x202F;&#x00B1;&#x202F;17.83&#x202F;years, of whom 20.29% met the criteria for hyperuricemia. The sex-specific characteristics and dietary consumption of participants across quintiles of dietary retinol intake are summarized in <xref ref-type="table" rid="tab1">Table 1</xref>. Males and females showed significant differences in age, BMI, waist circumference, alcohol intake, smoking status, physical activity, urbanization, hypertension, diabetes, and dietary intake of various nutrients.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Sex-specific characteristics and dietary consumption of the CHNS of rentinol intake&#x002A; (<italic>n</italic>&#x202F;=&#x202F;4,658).</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th align="center" valign="top" colspan="3">Male</th>
<th align="center" valign="top" colspan="3">Female</th>
</tr>
<tr>
<th/>
<th align="center" valign="top">Quintile 1</th>
<th align="center" valign="top">Quintile 3</th>
<th align="center" valign="top">Quintile 5</th>
<th align="center" valign="top">Quintile 1</th>
<th align="center" valign="top">Quintile 3</th>
<th align="center" valign="top">Quintile 5</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Participants (n)</td>
<td align="center" valign="middle">412</td>
<td align="center" valign="middle">434</td>
<td align="center" valign="middle">478</td>
<td align="center" valign="middle">519</td>
<td align="center" valign="middle">500</td>
<td align="center" valign="middle">456</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">Characteristics</td>
</tr>
<tr>
<td align="left" valign="middle">Age (years)</td>
<td align="center" valign="middle">45.11 (19.39)</td>
<td align="center" valign="middle">40.48 (19.88)</td>
<td align="center" valign="middle">44.21 (18.73)</td>
<td align="center" valign="middle">49.10 (16.47)</td>
<td align="center" valign="middle">46.74 (16.44)</td>
<td align="center" valign="middle">44.30 (13.95)</td>
</tr>
<tr>
<td align="left" valign="middle">BMI (kg/m<sup>2</sup>)</td>
<td align="center" valign="middle">21.53 (3.26)</td>
<td align="center" valign="middle">21.42 (3.81)</td>
<td align="center" valign="middle">21.98 (3.70)</td>
<td align="center" valign="middle">22.00 (3.39)</td>
<td align="center" valign="middle">22.57 (3.64)</td>
<td align="center" valign="middle">22.97 (3.10)</td>
</tr>
<tr>
<td align="left" valign="middle">Waist (cm)</td>
<td align="center" valign="middle">77.38 (10.59)</td>
<td align="center" valign="middle">78.72 (12.14)</td>
<td align="center" valign="middle">79.84 (11.00)</td>
<td align="center" valign="middle">77.59 (10.35)</td>
<td align="center" valign="middle">78.30 (11.38)</td>
<td align="center" valign="middle">79.58 (10.91)</td>
</tr>
<tr>
<td align="left" valign="middle">Alcohol intake (g/d)</td>
<td align="center" valign="middle">0.00 (0.00)</td>
<td align="center" valign="middle">5.04 (27.18)</td>
<td align="center" valign="middle">0.49 (3.47)</td>
<td align="center" valign="middle">0.00 (0.00)</td>
<td align="center" valign="middle">1.46 (10.13)</td>
<td align="center" valign="middle">0.13 (1.63)</td>
</tr>
<tr>
<td align="left" valign="middle">Current smoking (%)</td>
<td align="center" valign="middle">229 (16.65)</td>
<td align="center" valign="middle">262 (19.05)</td>
<td align="center" valign="middle">284 (20.65)</td>
<td align="center" valign="middle">8 (28.57)</td>
<td align="center" valign="middle">7 (25.00)</td>
<td align="center" valign="middle">5 (17.86)</td>
</tr>
<tr>
<td align="left" valign="middle">Physical activity (h/week)</td>
<td align="center" valign="middle">33.49 (20.19)</td>
<td align="center" valign="middle">38.86 (20.71)</td>
<td align="center" valign="middle">33.67 (20.11)</td>
<td align="center" valign="middle">34.23 (22.06)</td>
<td align="center" valign="middle">29.08 (19.16)</td>
<td align="center" valign="middle">29.22 (22.34)</td>
</tr>
<tr>
<td align="left" valign="middle">Urban [n (%)]</td>
<td align="center" valign="middle">56 (2.56)</td>
<td align="center" valign="middle">121 (5.54)</td>
<td align="center" valign="middle">115 (5.26)</td>
<td align="center" valign="middle">83 (3.36)</td>
<td align="center" valign="middle">154 (6.23)</td>
<td align="center" valign="middle">120 (4.85)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">Hypertension (%)</td>
</tr>
<tr>
<td align="left" valign="middle">Yes</td>
<td align="center" valign="middle">41 (1.96)</td>
<td align="center" valign="middle">18 (0.86)</td>
<td align="center" valign="middle">25 (1.19)</td>
<td align="center" valign="middle">27 (1.12)</td>
<td align="center" valign="middle">27 (1.12)</td>
<td align="center" valign="middle">20 (0.83)</td>
</tr>
<tr>
<td align="left" valign="middle">Do not know</td>
<td align="center" valign="middle">5 (0.24)</td>
<td align="center" valign="middle">0 (0.00)</td>
<td align="center" valign="middle">2 (0.10)</td>
<td align="center" valign="middle">1 (0.04)</td>
<td align="center" valign="middle">0 (0.00)</td>
<td align="center" valign="middle">0 (0.00)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">Diabetes (%)</td>
</tr>
<tr>
<td align="left" valign="middle">Yes</td>
<td align="center" valign="middle">11 (0.58)</td>
<td align="center" valign="middle">1 (0.05)</td>
<td align="center" valign="middle">4 (0.21)</td>
<td align="center" valign="middle">3 (0.14)</td>
<td align="center" valign="middle">14 (0.64)</td>
<td align="center" valign="middle">0 (0.00)</td>
</tr>
<tr>
<td align="left" valign="middle">Do not know</td>
<td align="center" valign="middle">4 (0.21)</td>
<td align="center" valign="middle">0 (0.00)</td>
<td align="center" valign="middle">2 (0.11)</td>
<td align="center" valign="middle">1 (0.05)</td>
<td align="center" valign="middle">0 (0.00)</td>
<td align="center" valign="middle">0 (0.00)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">Dietary intake</td>
</tr>
<tr>
<td align="left" valign="middle">Energy (kcal/day)</td>
<td align="center" valign="middle">1734.40 (581.14)</td>
<td align="center" valign="middle">1924.46(693.66)</td>
<td align="center" valign="middle">2234.32 (701.18)</td>
<td align="center" valign="middle">1548.66 (551.74)</td>
<td align="center" valign="middle">1714.84 (688.15)</td>
<td align="center" valign="middle">2294.37 (795.43)</td>
</tr>
<tr>
<td align="left" valign="middle">Carbohydrate (g/day)</td>
<td align="center" valign="middle">229.08 (94.96)</td>
<td align="center" valign="middle">224.99 (88.82)</td>
<td align="center" valign="middle">244.93 (107.59)</td>
<td align="center" valign="middle">193.96 (74.00)</td>
<td align="center" valign="middle">206.03 (107.65)</td>
<td align="center" valign="middle">242.63 (119.24)</td>
</tr>
<tr>
<td align="left" valign="middle">Fat intake (g/day)</td>
<td align="center" valign="middle">66.05 (49.47)</td>
<td align="center" valign="middle">84.80 (47.63)</td>
<td align="center" valign="middle">109.21 (55.78)</td>
<td align="center" valign="middle">64.69 (37.98)</td>
<td align="center" valign="middle">75.36 (39.73)</td>
<td align="center" valign="middle">116.44 (70.36)</td>
</tr>
<tr>
<td align="left" valign="middle">Protein intake (g/day)</td>
<td align="center" valign="middle">55.04 (23.84)</td>
<td align="center" valign="middle">56.43 (21.30)</td>
<td align="center" valign="middle">67.12 (24.82)</td>
<td align="center" valign="middle">47.97 (22.44)</td>
<td align="center" valign="middle">50.24 (19.15)</td>
<td align="center" valign="middle">68.58 (28.00)</td>
</tr>
<tr>
<td align="left" valign="middle">Fiber intake (g/day)</td>
<td align="center" valign="middle">11.83 (13.56)</td>
<td align="center" valign="middle">11.00 (6.66)</td>
<td align="center" valign="middle">17.73 (9.61)</td>
<td align="center" valign="middle">9.39 (8.55)</td>
<td align="center" valign="middle">10.74 (6.45)</td>
<td align="center" valign="middle">22.59 (15.19)</td>
</tr>
<tr>
<td align="left" valign="middle">Cholesterol (mg)</td>
<td align="center" valign="middle">109.90 (105.12)</td>
<td align="center" valign="middle">244.69 (231.47)</td>
<td align="center" valign="middle">275.80 (199.45)</td>
<td align="center" valign="middle">132.46 (144.70)</td>
<td align="center" valign="middle">183.07 (135.15)</td>
<td align="center" valign="middle">256.41 (179.34)</td>
</tr>
<tr>
<td align="left" valign="middle">Vitamin C (mg/day)</td>
<td align="center" valign="middle">44.29 (30.60)</td>
<td align="center" valign="middle">65.57 (36.87)</td>
<td align="center" valign="middle">96.08 (41.31)</td>
<td align="center" valign="middle">37.19 (25.58)</td>
<td align="center" valign="middle">62.50 (34.44)</td>
<td align="center" valign="middle">107.56 (54.48)</td>
</tr>
<tr>
<td align="left" valign="middle">Vitamin E (mg/day)</td>
<td align="center" valign="middle">25.33 (35.07)</td>
<td align="center" valign="middle">27.38 (25.10)</td>
<td align="center" valign="middle">27.86 (18.85)</td>
<td align="center" valign="middle">22.65 (29.94)</td>
<td align="center" valign="middle">23.67 (18.46)</td>
<td align="center" valign="middle">30.57 (23.57)</td>
</tr>
<tr>
<td align="left" valign="middle">Magnesium (mg/day)</td>
<td align="center" valign="middle">223.37 (173.89)</td>
<td align="center" valign="middle">188.80 (117.29)</td>
<td align="center" valign="middle">254.65 (131.57)</td>
<td align="center" valign="middle">176.63 (123.28)</td>
<td align="center" valign="middle">178.55 (121.91)</td>
<td align="center" valign="middle">273.53 (152.70)</td>
</tr>
<tr>
<td align="left" valign="middle">Iron intake (mg/day)</td>
<td align="center" valign="middle">20.27 (10.98)</td>
<td align="center" valign="middle">21.68 (11.25)</td>
<td align="center" valign="middle">25.89 (9.20)</td>
<td align="center" valign="middle">16.15 (7.65)</td>
<td align="center" valign="middle">18.17 (8.31)</td>
<td align="center" valign="middle">26.55 (10.13)</td>
</tr>
<tr>
<td align="left" valign="middle">Zinc intake (mg/day)</td>
<td align="center" valign="middle">9.84 (4.30)</td>
<td align="center" valign="middle">10.36 (3.91)</td>
<td align="center" valign="middle">12.22 (4.70)</td>
<td align="center" valign="middle">7.95 (3.41)</td>
<td align="center" valign="middle">8.87 (3.46)</td>
<td align="center" valign="middle">12.71 (4.72)</td>
</tr>
<tr>
<td align="left" valign="middle">Vitamin A (&#x00B5;g RE)</td>
<td align="center" valign="middle">72.82 (28.26)</td>
<td align="center" valign="middle">355.09 (63.01)</td>
<td align="center" valign="middle">1258.58 (494.74)</td>
<td align="center" valign="middle">74.35 (31.81)</td>
<td align="center" valign="middle">358.83 (66.56)</td>
<td align="center" valign="middle">1338.52 (626.55)</td>
</tr>
<tr>
<td align="left" valign="middle">Fish (g/day)</td>
<td align="center" valign="middle">6.42 (26.79)</td>
<td align="center" valign="middle">3.10 (15.57)</td>
<td align="center" valign="middle">16.39 (43.98)</td>
<td align="center" valign="middle">4.04 (16.67)</td>
<td align="center" valign="middle">4.41 (19.81)</td>
<td align="center" valign="middle">11.64 (32.70)</td>
</tr>
<tr>
<td align="left" valign="middle">Dairy products (g/day)</td>
<td align="center" valign="middle">7.39 (27.57)</td>
<td align="center" valign="middle">14.64 (49.32)</td>
<td align="center" valign="middle">7.90 (33.91)</td>
<td align="center" valign="middle">4.59 (16.73)</td>
<td align="center" valign="middle">7.98 (34.03)</td>
<td align="center" valign="middle">4.86 (19.69)</td>
</tr>
<tr>
<td align="left" valign="middle">Egg (g/day)</td>
<td align="center" valign="middle">3.50 (8.40)</td>
<td align="center" valign="middle">22.92 (34.55)</td>
<td align="center" valign="middle">20.27 (27.69)</td>
<td align="center" valign="middle">6.51 (9.89)</td>
<td align="center" valign="middle">15.88 (20.87)</td>
<td align="center" valign="middle">12.47 (19.11)</td>
</tr>
<tr>
<td align="left" valign="middle">Dark vegetables (g/day)</td>
<td align="center" valign="middle">7.58 (13.41)</td>
<td align="center" valign="middle">43.68 (42.99)</td>
<td align="center" valign="middle">118.30 (107.16)</td>
<td align="center" valign="middle">8.69 (17.03)</td>
<td align="center" valign="middle">50.70 (49.86)</td>
<td align="center" valign="middle">116.91 (112.54)</td>
</tr>
<tr>
<td align="left" valign="middle">Organ meats (g/day)</td>
<td align="center" valign="middle">0.00 (0.00)</td>
<td align="center" valign="middle">0.38 (4.56)</td>
<td align="center" valign="middle">2.37 (9.88)</td>
<td align="center" valign="middle">0.04 (0.91)</td>
<td align="center" valign="middle">0.29 (3.50)</td>
<td align="center" valign="middle">2.07 (9.09)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>&#x002A;Dietary data were collected using a three-day 24-h recall method, combined with a food inventory method.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec14">
<label>3.2</label>
<title>Association between retinol intake and hyperuricemia</title>
<p>The logistic regression analysis demonstrated a positive association between dietary retinol intake and the risk of hyperuricemia (<xref ref-type="table" rid="tab2">Table 2</xref>). In males, the odds ratios (ORs) for hyperuricemia across increasing quintiles of retinol intake were 1.13 (95% CI: 0.81&#x2013;1.58), 0.87 (95% CI: 0.62&#x2013;1.22), 1.59 (95% CI: 1.17&#x2013;2.16), and 2.31 (95% CI: 1.72&#x2013;3.12), respectively, compared to the lowest quintile, with a significant trend (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.0001) in the fully adjusted model. In females, the ORs were 1.14 (95% CI: 0.78&#x2013;1.67), 1.49 (95% CI: 1.03&#x2013;2.16), 2.00 (95% CI: 1.39&#x2013;2.88), and 1.48 (95% CI: 1.01&#x2013;2.16), respectively, with a significant trend (<italic>p</italic>&#x202F;=&#x202F;0.0022) in the fully adjusted model. The restricted cubic spline analysis revealed a significant dose&#x2013;response relationship between dietary retinol intake and the risk of hyperuricemia. The odds of hyperuricemia increased significantly when dietary retinol intake exceeded 3,538&#x202F;IU/day for males and 4,504&#x202F;IU/day for females (<xref ref-type="fig" rid="fig1">Figure 1</xref>).</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Dose&#x2013;response relationship between dietary retinol intake and hyperuricemia. Panel <bold>A</bold> depicts data for men, while panel <bold>B</bold> shows data for women. The association was adjusted for age, residence, diabetes, BMI, educational level, smoking status, alcohol consumption, physical activity, total energy intake, fat (quintiles), dietary cholesterol (quintiles), dietary fiber (quintiles), and mutual adjustment for protein, and BMI (quintiles). The solid line and blue shading represent the estimated odds ratios (ORs) and their 95% confidence intervals (CIs).</p>
</caption>
<graphic xlink:href="fnut-12-1508774-g001.tif"/>
</fig>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>ORs (95% CIs) for hyperuricemia according to quintiles of dietary retinol intake.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th align="center" valign="top">Quintile 1</th>
<th align="center" valign="top">Quintile 2</th>
<th align="center" valign="top">Quintile 3</th>
<th align="center" valign="top">Quintile 4</th>
<th align="center" valign="top">Quintile 5</th>
<th align="center" valign="top">
<italic>p</italic>
</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" colspan="7">Male</td>
</tr>
<tr>
<td align="left" valign="middle">Model 1</td>
<td align="center" valign="middle">1.00</td>
<td align="center" valign="middle">1.13 (0.81&#x2013;1.58)</td>
<td align="center" valign="middle">0.87 (0.62&#x2013;1.22)</td>
<td align="center" valign="middle">1.59 (1.17&#x2013;2.16)</td>
<td align="center" valign="middle">2.31 (1.72&#x2013;3.12)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="middle">Model 2</td>
<td align="center" valign="middle">1.00</td>
<td align="center" valign="middle">1.17 (0.82&#x2013;1.68)</td>
<td align="center" valign="middle">0.87 (0.61&#x2013;1.26)</td>
<td align="center" valign="middle">1.58 (1.13&#x2013;2.20)</td>
<td align="center" valign="middle">2.28 (1.65&#x2013;3.16)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="middle">Model 3</td>
<td align="center" valign="middle">1.00</td>
<td align="center" valign="middle">1.15 (0.81&#x2013;1.64)</td>
<td align="center" valign="middle">0.84 (0.59&#x2013;1.21)</td>
<td align="center" valign="middle">1.58 (1.13&#x2013;2.19)</td>
<td align="center" valign="middle">2.31 (1.67&#x2013;3.18)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="middle">Model 4</td>
<td align="center" valign="middle">1.00</td>
<td align="center" valign="middle">1.17 (0.82&#x2013;1.68)</td>
<td align="center" valign="middle">0.87 (0.61&#x2013;1.26)</td>
<td align="center" valign="middle">1.58 (1.13&#x2013;2.20)</td>
<td align="center" valign="middle">2.28 (1.65&#x2013;3.16)</td>
<td align="center" valign="middle">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">Female</td>
</tr>
<tr>
<td align="left" valign="middle">Model 1</td>
<td align="center" valign="middle">1.00</td>
<td align="center" valign="middle">1.14 (0.78&#x2013;1.67)</td>
<td align="center" valign="middle">1.49 (1.03&#x2013;2.16)</td>
<td align="center" valign="middle">2.00 (1.39&#x2013;2.88)</td>
<td align="center" valign="middle">1.48 (1.01&#x2013;2.16)</td>
<td align="center" valign="middle">0.0016</td>
</tr>
<tr>
<td align="left" valign="middle">Model 2</td>
<td align="center" valign="middle">1.00</td>
<td align="center" valign="middle">1.14 (0.78&#x2013;1.67)</td>
<td align="center" valign="middle">1.49 (1.03&#x2013;2.16)</td>
<td align="center" valign="middle">2.00 (1.39&#x2013;2.88)</td>
<td align="center" valign="middle">1.48 (1.01&#x2013;2.16)</td>
<td align="center" valign="middle">0.0012</td>
</tr>
<tr>
<td align="left" valign="middle">Model 3</td>
<td align="center" valign="middle">1.00</td>
<td align="center" valign="middle">1.24 (0.82&#x2013;1.86)</td>
<td align="center" valign="middle">1.54 (1.03&#x2013;2.30)</td>
<td align="center" valign="middle">2.11 (1.43&#x2013;3.12)</td>
<td align="center" valign="middle">1.58 (1.05&#x2013;2.37)</td>
<td align="center" valign="middle">0.0018</td>
</tr>
<tr>
<td align="left" valign="middle">Model 4</td>
<td align="center" valign="middle">1.00</td>
<td align="center" valign="middle">1.35 (0.89&#x2013;2.05)</td>
<td align="center" valign="middle">1.67 (1.10&#x2013;2.52)</td>
<td align="center" valign="middle">2.21 (1.48&#x2013;3.31)</td>
<td align="center" valign="middle">1.72 (1.13&#x2013;2.61)</td>
<td align="center" valign="middle">0.0022</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Model 1: age (5-year category). Model 2: model 1 adjustments plus urban (yes or no), diabetes (yes or no), current smoking (never, past, and current), alcohol intake (quintiles), physical activity (quintiles), and total energy intake (quintiles). Model 3: model 2 adjustments plus fat (quintiles), dietary cholesterol (quintiles), dietary fiber (quintiles), and mutual adjustment for protein. Model 4: model 3 adjustments plus BMI (quintiles).</p>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec sec-type="discussion" id="sec15">
<label>4</label>
<title>Discussion</title>
<p>Our study reveals that increased dietary retinol intake is linked to a higher prevalence of hyperuricemia, especially in men. Additionally, a J-shaped dose&#x2013;response relationship between hyperuricemia and dietary retinol was observed. This suggests that excessive intake of retinol may potentially elevate uric acid levels. Previous studies exploring the relationship between retinol intake and hyperuricemia or serum uric acid levels relied on cross-sectional analyses. Data from the 1988&#x2013;1994 NHANES highlighted a positive correlation between serum retinol levels and uric acid in the U.S. adult population (<xref ref-type="bibr" rid="ref19">19</xref>). Similarly, research conducted among Korean adults robusted the results, demonstrating that higher retinol intake was associated with elevated uric acid levels (<xref ref-type="bibr" rid="ref18">18</xref>, <xref ref-type="bibr" rid="ref36">36</xref>). Moreover, the use of isotretinoin, a retinoid medication for acne treatment, has been linked to increased uric acid levels, further supporting this relationship (<xref ref-type="bibr" rid="ref37">37</xref>). The mechanistic link between retinol levels and hyperuricemia remains inadequately elucidated. One plausible explanation involves the role of elevated serum retinol in enhancing xanthine oxidase activity. This enzyme not only catalyzes the conversion of retinol to retinoic acid but also facilitates the oxidation of xanthine, leading to increased uric acid production (<xref ref-type="bibr" rid="ref38">38</xref>, <xref ref-type="bibr" rid="ref39">39</xref>). However, to our knowledge, no prospective studies have yet explored the association between individual dietary retinol intake and uric acid levels or hyperuricemia.</p>
<p>The gender-stratified analysis highlights a pronounced susceptibility among men to hyperuricemia associated with elevated retinol intake. This finding aligns with established literature, which underscores the pivotal role of hormonal modulation in uric acid homeostasis. Specifically, prior studies have elucidated that estrogen facilitates uric acid excretion, thereby conferring a protective advantage against hyperuricemia in premenopausal women (<xref ref-type="bibr" rid="ref40">40</xref>, <xref ref-type="bibr" rid="ref41">41</xref>). Conversely, testosterone has been implicated in upregulating uric acid synthesis, potentially exacerbating the risk of hyperuricemia in men (<xref ref-type="bibr" rid="ref42">42</xref>). These results underscore the necessity for gender-specific dietary recommendations to mitigate the risk of hyperuricemia, particularly in populations with high retinol consumption.</p>
<p>Dose&#x2013;response analysis revealed that exceeding the recommended dietary retinol intake (3,538&#x202F;IU/day for men and 4,504&#x202F;IU/day for women) was linked to a higher prevalence of hyperuricemia, regardless of dietary supplement use. These values notably exceed the current recommended daily intakes of 3,000&#x202F;IU for men and 2,310&#x202F;IU for women (<xref ref-type="bibr" rid="ref43">43</xref>), highlighting the potential health risks of excessive consumption. These findings are consistent with previous studies indicating that excessive vitamin A can influence metabolic pathways related to uric acid production and excretion (<xref ref-type="bibr" rid="ref44">44</xref>). Although hypervitaminosis A is uncommon under typical dietary conditions, the rising prevalence of nutritional supplements as a primary source of vitamins raises the possibility of inadvertent overconsumption. For instance, during the 2003&#x2013;2006 NHANES survey, 53% of participants reported using dietary supplements, with 33% specifically consuming multivitamin/multimineral products that often contain retinol (<xref ref-type="bibr" rid="ref45">45</xref>). However, this pattern differs significantly in our study population from Southwest China, a lower-income region where supplement use is minimal. According to the 2010&#x2013;2012 CNHS survey, only 0.71% (95% CI: 0.49&#x2013;0.94%) of the Chinese population aged 6 and older reported using nutritional supplements in the past month, with usage rates in impoverished areas as low as 0.09% (<xref ref-type="bibr" rid="ref46">46</xref>). This low prevalence reflects both economic constraints and adherence to Chinese dietary guidelines, which emphasize obtaining nutrients primarily from food sources rather than supplements (<xref ref-type="bibr" rid="ref47">47</xref>). Given the limited supplement use in our study population, we did not include this variable in the main analysis. While this aligns with local dietary patterns, the lack of comprehensive supplement use data represents a limitation that should be addressed in future research, particularly as supplement use patterns may evolve with economic development.</p>
<p>Our findings contribute to the growing body of evidence supporting a positive association between retinol intake and hyperuricemia. However, the relationship appears to vary across different populations, highlighting the importance of population-specific factors in this association. For instance, studies from different regions of China have yielded varying results: while research in northern China observed a positive correlation between serum vitamin A levels and uric acid concentrations in adults (<xref ref-type="bibr" rid="ref48">48</xref>), a cross-sectional survey in Taiwan found no significant association between retinol intake and hyperuricemia (<xref ref-type="bibr" rid="ref23">23</xref>). Similarly, a study conducted in Korea reported lower dietary retinol intake among individuals with hyperuricemia (<xref ref-type="bibr" rid="ref21">21</xref>). These disparate findings may be partly explained by regional dietary habits. The distinctive dietary characteristics in Southwest China, characterized by lower consumption of vegetables, fruit, and animal products, along with a higher intake of grain and oil (<xref ref-type="bibr" rid="ref49">49</xref>), may uniquely influence both retinol intake and uric acid metabolism. Such regional variations in dietary habits underscore the importance of considering local dietary contexts when developing nutritional guidelines for hyperuricemia prevention.</p>
<p>Additionally, results in the present study indicate that individuals with higher retinol intake frequently consume more dark vegetables, organ meats, and fish. These consumption habits possibly reflect broader lifestyle choices that influence hyperuricemia risk. Therefore, we adjusted for potential confounders, including physical activity, smoking, and alcohol consumption, to more accurately assess the relationship between retinol intake and hyperuricemia. On the other hand, understanding the influence of lifestyle factors on retinol intake and hyperuricemia is crucial for developing effective prevention strategies. Physical activity represents another critical lifestyle factor in this relationship, as regular exercise has been shown to help maintain healthy uric acid levels (<xref ref-type="bibr" rid="ref50">50</xref>), whereas sedentary behavior may increase hyperuricemia risk (<xref ref-type="bibr" rid="ref51">51</xref>). These findings suggest that managing hyperuricemia requires a comprehensive lifestyle approach. Indeed, previous research has demonstrated that combined interventions incorporating balanced dietary choices, regular physical activity, limited alcohol consumption, and weight management are more effective in preventing hyperuricemia than modifications to single factors (<xref ref-type="bibr" rid="ref52">52</xref>). This integrated approach to lifestyle management may be particularly important for individuals with elevated retinol intake, as it involves multiple pathways that influence uric acid metabolism.</p>
<p>In summary, this study provides valuable insights into the association between dietary retinol intake and hyperuricemia within a Southwest China population, demonstrating a significant relationship through comprehensive dietary assessments and a large, representative sample. The dose&#x2013;response analysis reveals specific threshold levels associated with increased risk, while gender-stratified results highlight the need for sex-specific recommendations. Despite methodological limitations inherent to our cross-sectional design and dietary assessment methods, which preclude causal inference and may introduce recall bias, these findings make a substantial contribution to our understanding of the retinol-hyperuricemia relationship. The regional dietary patterns characteristic of Southwest China, while potentially limiting broader generalizability, offer unique insights into population-specific nutritional factors affecting hyperuricemia. Future longitudinal and experimental studies are crucial to validate these observations and elucidate underlying mechanisms, particularly focusing on population-specific dietary patterns and their impact on hyperuricemia risk.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec16">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec sec-type="ethics-statement" id="sec17">
<title>Ethics statement</title>
<p>The CHNS was approved by the institutional review boards of the University of North Carolina at Chapel Hill and the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.</p>
</sec>
<sec sec-type="author-contributions" id="sec18">
<title>Author contributions</title>
<p>YLia: Data curation, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. TQ: Conceptualization, Methodology, Writing &#x2013; review &#x0026; editing. XN: Conceptualization, Software, Writing &#x2013; review &#x0026; editing. LY: Investigation, Writing &#x2013; review &#x0026; editing. TY: Investigation, Writing &#x2013; review &#x0026; editing. YLiu: Data curation, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec sec-type="funding-information" id="sec19">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study was funded by the National Natural Science Foundation of China (82160616), Guizhou Medical University Ph.D. Start Fund Project (gyfybsky-2021-22), Guizhou Science and Technology Department ([2024] 071).</p>
</sec>
<sec sec-type="COI-statement" id="sec20">
<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="sec21">
<title>Generative AI statement</title>
<p>The authors declare that no Gen AI was used in the creation of this manuscript.</p>
</sec>
<sec sec-type="disclaimer" id="sec22">
<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>
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