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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Med.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Medicine</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Med.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2296-858X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmed.2025.1596799</article-id><article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading"><subject>Original Research</subject></subj-group>
</article-categories>
<title-group>
<article-title>Association between serum carotenoid concentrations and risk of major age-related eye diseases among middle-aged and older adults</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Che</surname>
<given-names>Songtian</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Ma</surname>
<given-names>Yan</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Cao</surname>
<given-names>Jinfeng</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="aff2" ref-type="aff"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3010042"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
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<aff id="aff1"><label>1</label><institution>Department of Ophthalmology, The Second Hospital of Jilin University</institution>, <city>Changchun</city>, <country country="cn">China</country></aff>
<aff id="aff2"><label>2</label><institution>Jilin Provincial Engineering Laboratory of Ophthalmology</institution>, <city>Changchun</city>, <country country="cn">China</country></aff>
<author-notes><corresp id="c001"><label>&#x002A;</label>Correspondence: Jinfeng Cao, <email xlink:href="mailto:jcao@jlu.edu.cn">jcao@jlu.edu.cn</email></corresp></author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2025-12-01">
<day>01</day>
<month>12</month>
<year>2025</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2025</year>
</pub-date>
<volume>12</volume>
<elocation-id>1596799</elocation-id>
<history>
<date date-type="received">
<day>24</day>
<month>03</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>20</day>
<month>10</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2025 Che, Ma and Cao.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Che, Ma and Cao</copyright-holder>
<license><ali:license_ref start_date="2025-12-01">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. 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.</license-p>
</license>
</permissions>
<abstract>
<sec id="sec1">
<title>Background</title>
<p>Age-related eye diseases are the main causes of progressive and irreversible vision loss in aging populations worldwide. Carotenoids, as a group of common natural antioxidants, can suppress free radicals produced by complex physiological reactions, thereby protecting the eyes from the effects of oxidative stress, cell apoptosis, and mitochondrial dysfunction. The present study aims to explore the association between serum carotenoid concentrations and risk of major age-related eye diseases among middle-aged and older adults in the United States.</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>This study involved 1,478 participants aged &#x2265;50&#x202F;years from the 2005&#x2013;2006&#x202F;cycles of the National Health and Nutrition Examination Survey (NHANES). Multivariate logistic regression was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of prevalence of cataract, glaucoma, diabetic retinopathy, and age-related macular degeneration (AMD) in relation to serum carotenoid concentrations.</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>Compared to participants in the first quartile, those in highest quartile of serum <italic>&#x03B1;</italic>-carotene (OR: 0.37; 95% CI: 0.21&#x2013;0.64), <italic>&#x03B2;</italic>-carotene (OR: 0.57; 95% CI: 0.33&#x2013;0.95), lutein/zeaxanthin (OR: 0.45; 95% CI: 0.27&#x2013;0.76), and total carotenoid (OR: 0.58; 95% CI: 0.35&#x2013;0.97) were negatively associated with risk of cataract; those in highest quartile of serum <italic>&#x03B2;</italic>-carotene (OR: 0.30; 95% CI: 0.11&#x2013;0.77) and &#x03B2;-cryptoxanthin (OR: 0.28; 95% CI: 0.12&#x2013;0.68) were negatively associated with risk of diabetic retinopathy; and those in highest quartile of lycopene (OR: 0.37; 95% CI: 0.18&#x2013;0.78) was negatively associated with risk of AMD. In addition, subgroup analysis results indicated that participants in highest quartile of serum <italic>&#x03B1;</italic>-carotene (OR: 0.16; 95% CI: 0.08&#x2013;0.32), <italic>&#x03B2;</italic>-carotene (OR: 0.40; 95% CI: 0.21&#x2013;0.75), lycopene (OR: 0.46; 95% CI: 0.24&#x2013;0.87), lutein/zeaxanthin (OR: 0.45; 95% CI: 0.25&#x2013;0.84), and total carotenoid (OR: 0.41; 95% CI: 0.22&#x2013;0.77) concentrations were negatively associated with risk of any ocular disease among female participants. By contrast, no associations were observed among male participants.</p>
</sec>
<sec id="sec4">
<title>Conclusion</title>
<p>Our study demonstrated that higher serum concentrations of carotenoids were negatively associated with the risk of age-related eye diseases, particularly among middle-aged and older female participants.</p>
</sec>
</abstract>
<kwd-group>
<kwd>serum carotenoids</kwd>
<kwd>cataract</kwd>
<kwd>glaucoma</kwd>
<kwd>diabetic retinopathy</kwd>
<kwd>age-related macular degeneration</kwd>
<kwd>NHANES</kwd>
</kwd-group><funding-group><funding-statement>The author(s) declare that financial support was received for the research and/or publication of this article. This work was supported by the Health Special Fund of the Jilin Provincial Department of Finance (Project No. 2019SCZT020) and the Capacity Building for Jilin Provincial Ophthalmic Engineering Laboratory (Project No. 2022C006).</funding-statement></funding-group>
<counts>
<fig-count count="1"/>
<table-count count="4"/>
<equation-count count="0"/>
<ref-count count="54"/>
<page-count count="12"/>
<word-count count="8872"/>
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<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Ophthalmology</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec5">
<label>1</label>
<title>Introduction</title>
<p>With the rapid growth of middle-aged and older adult populations, the prevalence of common age-related eye diseases has increased, including cataract, glaucoma, diabetic retinopathy, and age-related macular degeneration (AMD), which are the main causes of progressive and irreversible vision loss in aging populations worldwide (<xref ref-type="bibr" rid="ref1 ref2 ref3">1&#x2013;3</xref>). Globally, 285 million people have moderate to severe visual impairment or blindness, of whom 65% of the visually impaired and 82% of all blind people are aged 50 or older (<xref ref-type="bibr" rid="ref4">4</xref>). In the United States, the prevalence of most eye diseases increases with age among individuals aged &#x2265;50&#x202F;years, and such diseases impose a substantial socioeconomic burden (<xref ref-type="bibr" rid="ref5">5</xref>). Furthermore, age-related eye diseases can reduce the quality of life of older adults and independently increase their mortality (<xref ref-type="bibr" rid="ref6 ref7 ref8">6&#x2013;8</xref>). Because of their overall health implications, age-related eye diseases are a major health concern among middle-aged and older adults, and new strategies for preventing or delaying disease progression must be identified.</p>
<p>Studies have reported that the cells of the tissues of the eyes are sensitive to oxidative stress, triggering and exacerbating age-related ocular abnormalities (<xref ref-type="bibr" rid="ref9">9</xref>). Carotenoids are a group of common natural antioxidants and fat-soluble phytochemicals that are synthesized only by specific microorganisms and plants (<xref ref-type="bibr" rid="ref10">10</xref>, <xref ref-type="bibr" rid="ref11">11</xref>). To the best of our knowledge, <italic>&#x03B1;</italic>-carotene, <italic>&#x03B2;</italic>-carotene, &#x03B2;-cryptoxanthin, lycopene, lutein, and zeaxanthin account for more than 95% of the carotenoids in circulation (<xref ref-type="bibr" rid="ref11">11</xref>, <xref ref-type="bibr" rid="ref12">12</xref>). Because ocular carotenoids absorb light in the visible light region, they protect the retina and lens from the potential photochemical damage caused by light exposure (<xref ref-type="bibr" rid="ref13">13</xref>, <xref ref-type="bibr" rid="ref14">14</xref>). Carotenoids can also suppress the free radicals produced by complex physiological reactions, thereby protecting the eyes from the effects of oxidative stress, cell apoptosis, mitochondrial dysfunction, and inflammation (<xref ref-type="bibr" rid="ref13">13</xref>). Several previous studies have reported that dietary carotenoid supplementation had a potential beneficial association with reduced risk of cataract, preserved macular health in glaucoma and promoted retinal health, and improved visual function in diabetic retinopathy (<xref ref-type="bibr" rid="ref15 ref16 ref17 ref18">15&#x2013;18</xref>). In addition, the Age-Related Eye Diseases Study (AREDS) Research Group demonstrated that dietary lutein/zeaxanthin supplementation was significantly associated with late AMD progression and can serve as an appropriate replacement for beta carotene, which increased the risk of lung cancer (<xref ref-type="bibr" rid="ref19">19</xref>, <xref ref-type="bibr" rid="ref20">20</xref>).</p>
<p>To date, the majority of previous studies have focused on the association between dietary carotenoid intake and eye diseases (<xref ref-type="bibr" rid="ref21">21</xref>, <xref ref-type="bibr" rid="ref22">22</xref>), whereas epidemiological evidence regarding the relationship between serum carotenoid concentrations and the risk of age-related eye diseases remains limited. Serum concentrations provide a direct measure of absorbed, metabolically processed carotenoids, reflecting interindividual differences in digestion, absorption, and metabolism that dietary assessments cannot capture. A cross-sectional study demonstrated that a higher concentration of serum <italic>&#x03B1;</italic>-carotene is associated with a lower risk of diabetic retinopathy (<xref ref-type="bibr" rid="ref23">23</xref>). Furthermore, higher blood concentrations of <italic>&#x03B1;</italic>-carotene, <italic>&#x03B2;</italic>-carotene, &#x03B2;-cryptoxanthin, lycopene, and lutein/zeaxanthin are associated with a lower risk of cataract among individuals aged &#x2265;50&#x202F;years (<xref ref-type="bibr" rid="ref24">24</xref>). A case&#x2013;control study reported that higher serum concentrations of carotenoids, particularly zeaxanthin and lycopene, were associated with a lower likelihood of developing exudative AMD in an older Chinese population (<xref ref-type="bibr" rid="ref25">25</xref>). Notably, most of the aforementioned studies have mainly focused on the association between the serum carotenoid concentration and single eye diseases in Asian populations. To date, few studies have comprehensively explored the association between serum carotenoids and various age-related eye diseases among populations in the United States.</p>
<p>In the present population-based cross-sectional study, we examined the association of the serum carotenoid concentration with the risk of major age-related eye diseases, including cataract, glaucoma, diabetic retinopathy, and AMD, in a nationally representative sample of the middle-aged and older adult population in the United States.</p>
</sec>
<sec sec-type="materials|methods" id="sec6">
<label>2</label>
<title>Materials and methods</title>
<sec id="sec7">
<label>2.1</label>
<title>Study population</title>
<p>The National Health and Nutrition Examination Survey (NHANES) is an ongoing cross-sectional study conducted by the National Center for Health Statistics (NCHS) at the Centers for Disease Control and Prevention (CDC) to assess the health and nutritional status of a nationally representative sample of the civilian population in the United States. Data from the 2005&#x2013;2006&#x202F;cycle of the NHANES were used for this analysis. The protocols for the NHANES study were approved by the Research Ethics Review Board of the NCHS. Each participant provided written informed consent.</p>
<p>In the NHANES 2005&#x2013;2006, there were a total of 10,348 participants, and the present analysis was limited to 2,214 participants aged 50 and older. We excluded participants with missing data for serum carotenoid concentrations (<italic>n</italic>&#x202F;=&#x202F;220) and major eye diseases (<italic>n</italic>&#x202F;=&#x202F;516), including cataract, glaucoma, diabetic retinopathy, and AMD. Finally, 1,478 participants were included in the present study.</p>
</sec>
<sec id="sec8">
<label>2.2</label>
<title>Assessment of carotenoids</title>
<p>Serum carotenoids, including <italic>&#x03B1;</italic>-carotene, <italic>&#x03B2;</italic>-carotene, &#x03B2;-cryptoxanthin, lycopene, and lutein/zeaxanthin, were quantified at the CDC&#x2019;s National Center for Environmental Health using validated high-performance liquid chromatography (HPLC) with multiwavelength photodiode-array absorbance detection. The laboratory procedures involved mixing serum with a buffer and ethanol containing internal standards&#x2014;retinyl butyrate and nonapreno-beta-carotene (C45)&#x2014;followed by extraction into hexane. The combined hexane extracts were then redissolved in ethyl acetate, diluted in mobile phase, and injected onto a C18 reversed-phase column for isocratic elution. Carotenoids were detected by absorbance at 450&#x202F;nm. The coefficient of variation (CV) was generally below 5% for <italic>&#x03B2;</italic>-carotene and below 20% for minor carotenoids. Total serum carotenoid concentration was calculated as the sum of the five individual carotenoids. Detailed quality control methods and analytical protocols have been described elsewhere (<xref ref-type="bibr" rid="ref12">12</xref>, <xref ref-type="bibr" rid="ref26">26</xref>).</p>
</sec>
<sec id="sec9">
<label>2.3</label>
<title>Assessment of major eye disease</title>
<p>The NHANES database provided retinal imaging results, which were used to examine the presence of diabetic retinopathy and AMD. Diabetic retinopathy was determined by any signs of retinopathy and the diagnosis of diabetes (<xref ref-type="bibr" rid="ref27">27</xref>). Based on the fundus photographs, the retinopathy was graded by four levels, including no retinopathy, mild non-proliferative retinopathy (NPR), moderate, or severe NPR. Diabetes was defined as a self-report of a previous diagnosis of the disease or a hemoglobin A<sub>1c</sub> (HbA<sub>1c</sub>) level&#x2265;6.5% according to the American Diabetes Association&#x2019;s diagnostic criteria for diabetes (<xref ref-type="bibr" rid="ref28">28</xref>). According to the modified Wisconsin Age-Related Maculopathy Grading Classification Scheme, early AMD is defined by the presence or absence of drusen and/or pigmentary abnormalities; late AMD is defined by exudative AMD signs and/or geographic atrophy. In the present study, participants were divided into two groups: no AMD and AMD. A range of quality control measures was implemented to ensure the accuracy and reliability of retinal image grading. Fundus images were assessed by a team of nine trained graders, including a preliminary grading coordinator, two preliminary graders, and six detail graders. Grading was conducted in a semi-quantitative manner using EyeQ Lite software, with high-resolution monitors for detailed evaluation. The process involved three stages: an initial review for detectable pathology, preliminary grading, and detailed grading. Each image was independently evaluated by at least two graders. In case of disagreement, the image was evaluated by an adjudicator who made a final decision. Further details are available in the NHANES Digital Grading Protocol.</p>
<p>Furthermore, NHANES provided self-reported personal interview data on vision status, including cataract and glaucoma. The cataract status in all participants was based on their answers to the question, &#x201C;Have you ever had a cataract operation?&#x201D; Glaucoma was defined by the question: &#x201C;Have you ever been told you had glaucoma, sometimes called high pressure in eyes?&#x201D; The questions were asked using the Computer-Assisted Personal Interviewing system (CAPI), which was programmed with built-in consistency checks to reduce data entry errors.</p>
</sec>
<sec id="sec10">
<label>2.4</label>
<title>Statistical analysis</title>
<p>Data were expressed as mean &#x00B1; standard deviation (SD) of continuous variables and numbers (percentages) of categorical variables. Demographic characteristics between quartiles of serum total carotenoid concentrations were compared by one-way ANOVA tests for continuous variables and chi-square tests for categoric variables. Univariate and multivariate logistic regression analyses were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of prevalence of cataract, glaucoma, diabetic retinopathy, and AMD in relation to serum carotenoid concentrations. <italic>p</italic>-values for trend were obtained by including the quartile number as a continuous variable in the regression model. The multivariate adjusted model was adjusted for age (continuous), sex (male or female), race/ethnicity (non-Hispanic white, black, Mexican-American, other Hispanic, or other race/ethnicity), education level (less than high school, high school or equivalent, college or above, or missing), family income-to-poverty ratio (FIR) (&#x003C;1.3, 1.3 to &#x2264;3.5, &#x003E;3.5, or missing), body mass index (BMI) (&#x003C;18.5, 18.5 to &#x003C;25, 25 to &#x003C;30, &#x2265;30&#x202F;kg/m<sup>2</sup>, or missing), drinking status (non-drinker or drinker), smoking status (never smoker, former smoker, current smoker, or missing), HbA<sub>1c</sub> (&#x003C;6.5%, &#x2265;6.5%, or missing), hypertension (yes, no, or missing), and hypercholesterolemia (yes, no, or missing). We selected these confounders on the basis of their associations with the outcomes of interest or a change in the effect estimate of more than 10% (<xref ref-type="bibr" rid="ref29">29</xref>, <xref ref-type="bibr" rid="ref30">30</xref>). Model goodness-of-fit was assessed using Akaike Information Criterion (AIC) and residual plots. We used the restricted cubic spline regression models to investigate dose&#x2013;response associations between serum <italic>&#x03B1;</italic>-carotene, <italic>&#x03B2;</italic>-carotene, &#x03B2;-cryptoxanthin, lycopene, lutein/zeaxanthin, and total carotenoid concentrations and risk of any ocular disease. Sensitivity analyses by excluding participants with missing data on covariates were also conducted. Furthermore, interaction and stratified analyses were conducted according to sex (male vs. female) and smoking status (never smoker vs. former or current smoker), and <italic>P</italic> for interaction was calculated using the likelihood ratio test. Significance for pre-specified subgroup interactions (sex and smoking status) was assessed using a Bonferroni-corrected threshold of a <italic>p</italic>-value of &#x003C; 0.025 to account for multiple testing. All statistical analyses were conducted using R Statistical Software (Version 4.2.2).</p>
</sec>
</sec>
<sec sec-type="results" id="sec11">
<label>3</label>
<title>Results</title>
<sec id="sec12">
<label>3.1</label>
<title>Demographic characteristics of the study participants</title>
<p>The demographic characteristics of participants are summarized in <xref ref-type="table" rid="tab1">Table 1</xref>. Among 1,478 participants, there were 775 (52.44%) males and 703 (47.56%) females, with an average age of 65.34&#x202F;&#x00B1;&#x202F;10.13&#x202F;years. There were differences in age, sex, race, education, FIR, BMI, smoking status, and proportion of alcohol drinkers, diabetes, and hypertension between quartiles of serum total carotenoid concentrations (all <italic>p</italic>&#x202F;&#x003C;&#x202F;0.05). Participants with higher serum total carotenoid concentrations were younger, more likely to be female and alcohol drinkers, less likely to be non-Hispanic whites, obese, and current smokers, and tended to have greater education and FIR level, a lower proportion of HbA1&#x202F;&#x2265;&#x202F;6.5% and hypertension. Comparison of serum carotenoid concentrations among participants, stratified by sex, is shown in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 1</xref>. The results showed that female participants have lower carotenoid levels compared to male participants.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Characteristics of participants by quartiles of serum total carotenoid concentrations.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th rowspan="2"/>
<th align="center" valign="top" colspan="5">Serum total carotenoid concentrations (&#x03BC;mol/L)</th>
</tr>
<tr>
<th align="center" valign="top">Total<break/>(<italic>n</italic>&#x202F;=&#x202F;1,478)</th>
<th align="center" valign="top">Quartile 1<break/>(<italic>n</italic>&#x202F;=&#x202F;370)</th>
<th align="center" valign="top">Quartile 2<break/>(<italic>n</italic>&#x202F;=&#x202F;368)</th>
<th align="center" valign="top">Quartile 3<break/>(<italic>n</italic>&#x202F;=&#x202F;370)</th>
<th align="center" valign="top">Quartile 4<break/>(<italic>n</italic>&#x202F;=&#x202F;370)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" colspan="6">Socioeconomics and health factors</td>
</tr>
<tr>
<td align="left" valign="middle">Age, year</td>
<td align="center" valign="middle">65.34&#x202F;&#x00B1;&#x202F;10.13</td>
<td align="center" valign="middle">66.52&#x202F;&#x00B1;&#x202F;10.45</td>
<td align="center" valign="middle">65.22&#x202F;&#x00B1;&#x202F;9.85</td>
<td align="center" valign="middle">65.35&#x202F;&#x00B1;&#x202F;10.20</td>
<td align="center" valign="middle">64.28&#x202F;&#x00B1;&#x202F;9.94</td>
</tr>
<tr>
<td align="left" valign="middle">Male sex, <italic>n</italic> (%)</td>
<td align="center" valign="middle">775 (52.44)</td>
<td align="center" valign="middle">219 (59.19)</td>
<td align="center" valign="middle">193 (52.45)</td>
<td align="center" valign="middle">198 (53.51)</td>
<td align="center" valign="middle">165 (44.59)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="6">Race/Ethnicity, <italic>n</italic> (%)</td>
</tr>
<tr>
<td align="left" valign="middle">Non-Hispanic white</td>
<td align="center" valign="middle">892 (60.35)</td>
<td align="center" valign="middle">240 (64.86)</td>
<td align="center" valign="middle">217 (58.97)</td>
<td align="center" valign="middle">215 (58.11)</td>
<td align="center" valign="middle">220 (59.46)</td>
</tr>
<tr>
<td align="left" valign="middle">Black</td>
<td align="center" valign="middle">305 (20.64)</td>
<td align="center" valign="middle">78 (21.08)</td>
<td align="center" valign="middle">89 (24.18)</td>
<td align="center" valign="middle">70 (18.92)</td>
<td align="center" valign="middle">68 (18.38)</td>
</tr>
<tr>
<td align="left" valign="middle">Mexican American</td>
<td align="center" valign="middle">217 (14.68)</td>
<td align="center" valign="middle">39 (10.54)</td>
<td align="center" valign="middle">53 (14.40)</td>
<td align="center" valign="middle">68 (18.38)</td>
<td align="center" valign="middle">57 (15.41)</td>
</tr>
<tr>
<td align="left" valign="middle">Other Hispanic</td>
<td align="center" valign="middle">27 (1.83)</td>
<td align="center" valign="middle">7 (1.89)</td>
<td align="center" valign="middle">2 (0.54)</td>
<td align="center" valign="middle">8 (2.16)</td>
<td align="center" valign="middle">10 (2.70)</td>
</tr>
<tr>
<td align="left" valign="middle">Other race/ethnicity</td>
<td align="center" valign="middle">37 (2.50)</td>
<td align="center" valign="middle">6 (1.62)</td>
<td align="center" valign="middle">7 (1.90)</td>
<td align="center" valign="middle">9 (2.43)</td>
<td align="center" valign="middle">15 (4.05)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="6">Education, <italic>n</italic> (%)</td>
</tr>
<tr>
<td align="left" valign="middle">Less than high school</td>
<td align="center" valign="middle">218 (14.75)</td>
<td align="center" valign="middle">66 (17.84)</td>
<td align="center" valign="middle">56 (15.22)</td>
<td align="center" valign="middle">48 (12.97)</td>
<td align="center" valign="middle">48 (12.97)</td>
</tr>
<tr>
<td align="left" valign="middle">High school or equivalent</td>
<td align="center" valign="middle">600 (40.60)</td>
<td align="center" valign="middle">174 (47.03)</td>
<td align="center" valign="middle">169 (45.92)</td>
<td align="center" valign="middle">147 (39.73)</td>
<td align="center" valign="middle">110 (29.73)</td>
</tr>
<tr>
<td align="left" valign="middle">College or above</td>
<td align="center" valign="middle">660 (44.65)</td>
<td align="center" valign="middle">130 (35.14)</td>
<td align="center" valign="middle">143 (38.86)</td>
<td align="center" valign="middle">175 (47.30)</td>
<td align="center" valign="middle">212 (57.30)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="6">Family income-to-poverty ratio, <italic>n</italic> (%)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x003C;1.3</td>
<td align="center" valign="middle">319 (22.80)</td>
<td align="center" valign="middle">118 (33.43)</td>
<td align="center" valign="middle">78 (22.41)</td>
<td align="center" valign="middle">69 (19.77)</td>
<td align="center" valign="middle">54 (15.47)</td>
</tr>
<tr>
<td align="left" valign="middle">1.3 to &#x2264;3.5</td>
<td align="center" valign="middle">564 (40.31)</td>
<td align="center" valign="middle">160 (45.33)</td>
<td align="center" valign="middle">137 (39.37)</td>
<td align="center" valign="middle">141 (40.40)</td>
<td align="center" valign="middle">126 (36.10)</td>
</tr>
<tr>
<td align="left" valign="middle">&#x003E;3.5</td>
<td align="center" valign="middle">516 (36.88)</td>
<td align="center" valign="middle">75 (21.25)</td>
<td align="center" valign="middle">133 (38.22)</td>
<td align="center" valign="middle">139 (39.83)</td>
<td align="center" valign="middle">169 (48.42)</td>
</tr>
<tr>
<td align="left" valign="middle">Missing</td>
<td align="center" valign="middle">79 (5.35)</td>
<td align="center" valign="middle">17 (4.59)</td>
<td align="center" valign="middle">20 (5.43)</td>
<td align="center" valign="middle">21 (5.68)</td>
<td align="center" valign="middle">21 (5.68)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="6">Body mass index, <italic>n</italic> (%)</td>
</tr>
<tr>
<td align="left" valign="top">&#x003C;18.5&#x202F;kg/m<sup>2</sup></td>
<td align="center" valign="middle">21 (1.43)</td>
<td align="center" valign="middle">7 (1.93)</td>
<td align="center" valign="middle">2 (0.55)</td>
<td align="center" valign="middle">3 (0.82)</td>
<td align="center" valign="middle">9 (2.45)</td>
</tr>
<tr>
<td align="left" valign="top">18.5 to &#x003C;25&#x202F;kg/m<sup>2</sup></td>
<td align="center" valign="middle">374 (25.55)</td>
<td align="center" valign="middle">81 (22.38)</td>
<td align="center" valign="middle">73 (19.95)</td>
<td align="center" valign="middle">79 (21.47)</td>
<td align="center" valign="middle">141 (38.32)</td>
</tr>
<tr>
<td align="left" valign="top">25 to &#x003C;30&#x202F;kg/m<sup>2</sup></td>
<td align="center" valign="middle">539 (36.82)</td>
<td align="center" valign="middle">122 (33.70)</td>
<td align="center" valign="middle">134 (36.61)</td>
<td align="center" valign="middle">149 (40.49)</td>
<td align="center" valign="middle">134 (36.41)</td>
</tr>
<tr>
<td align="left" valign="top">&#x2265;30&#x202F;kg/m<sup>2</sup></td>
<td align="center" valign="middle">530 (36.20)</td>
<td align="center" valign="middle">152 (41.99)</td>
<td align="center" valign="middle">157 (42.90)</td>
<td align="center" valign="middle">137 (37.23)</td>
<td align="center" valign="middle">84 (22.83)</td>
</tr>
<tr>
<td align="left" valign="top">Missing</td>
<td align="center" valign="middle">14 (0.95)</td>
<td align="center" valign="middle">8 (2.16)</td>
<td align="center" valign="middle">2 (0.54)</td>
<td align="center" valign="middle">2 (0.54)</td>
<td align="center" valign="middle">2 (0.54)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="6">Smoking status, <italic>n</italic> (%)</td>
</tr>
<tr>
<td align="left" valign="middle">Never smoker</td>
<td align="center" valign="middle">660 (44.81)</td>
<td align="center" valign="middle">125 (33.88)</td>
<td align="center" valign="middle">165 (45.21)</td>
<td align="center" valign="middle">171 (46.22)</td>
<td align="center" valign="middle">199 (53.93)</td>
</tr>
<tr>
<td align="left" valign="middle">Former smoker</td>
<td align="center" valign="middle">548 (37.20)</td>
<td align="center" valign="middle">146 (39.57)</td>
<td align="center" valign="middle">121 (33.15)</td>
<td align="center" valign="middle">148 (40.00)</td>
<td align="center" valign="middle">133 (36.04)</td>
</tr>
<tr>
<td align="left" valign="middle">Current smoker</td>
<td align="center" valign="middle">265 (17.99)</td>
<td align="center" valign="middle">98 (26.56)</td>
<td align="center" valign="middle">79 (21.64)</td>
<td align="center" valign="middle">51 (13.78)</td>
<td align="center" valign="middle">37 (10.03)</td>
</tr>
<tr>
<td align="left" valign="middle">Missing</td>
<td align="center" valign="middle">5 (0.34)</td>
<td align="center" valign="middle">1 (0.27)</td>
<td align="center" valign="middle">3 (0.82)</td>
<td align="center" valign="middle">0 (0.00)</td>
<td align="center" valign="middle">1 (0.27)</td>
</tr>
<tr>
<td align="left" valign="middle">Alcohol drinker, <italic>n</italic> (%)</td>
<td align="center" valign="middle">973 (67.29)</td>
<td align="center" valign="middle">245 (67.68)</td>
<td align="center" valign="middle">221 (61.39)</td>
<td align="center" valign="middle">243 (67.13)</td>
<td align="center" valign="middle">264 (72.93)</td>
</tr>
<tr>
<td align="left" valign="middle">Missing</td>
<td align="center" valign="middle">32 (2.17)</td>
<td align="center" valign="middle">8 (2.16)</td>
<td align="center" valign="middle">8 (2.17)</td>
<td align="center" valign="middle">8 (2.16)</td>
<td align="center" valign="middle">8 (2.16)</td>
</tr>
<tr>
<td align="left" valign="middle">Hemoglobin A<sub>1c</sub>&#x202F;&#x2265;&#x202F;6.5%, <italic>n</italic> (%)</td>
<td align="center" valign="middle">245 (16.58)</td>
<td align="center" valign="middle">87 (23.51)</td>
<td align="center" valign="middle">70 (19.02)</td>
<td align="center" valign="middle">47 (12.70)</td>
<td align="center" valign="middle">41 (11.08)</td>
</tr>
<tr>
<td align="left" valign="middle">Missing</td>
<td align="center" valign="middle">3 (0.20)</td>
<td align="center" valign="middle">1 (0.27)</td>
<td align="center" valign="middle">1 (0.27)</td>
<td align="center" valign="middle">0 (0.00)</td>
<td align="center" valign="middle">1 (0.27)</td>
</tr>
<tr>
<td align="left" valign="middle">Hypertension, <italic>n</italic> (%)</td>
<td align="center" valign="middle">745 (50.54)</td>
<td align="center" valign="middle">209 (56.49)</td>
<td align="center" valign="middle">203 (55.62)</td>
<td align="center" valign="middle">168 (45.53)</td>
<td align="center" valign="middle">165 (44.59)</td>
</tr>
<tr>
<td align="left" valign="middle">Missing</td>
<td align="center" valign="middle">4 (0.27)</td>
<td align="center" valign="middle">0 (0.00)</td>
<td align="center" valign="middle">3 (0.82)</td>
<td align="center" valign="middle">1 (0.27)</td>
<td align="center" valign="middle">0 (0.00)</td>
</tr>
<tr>
<td align="left" valign="middle">Hypercholesterolemia, <italic>n</italic> (%)</td>
<td align="center" valign="middle">677 (53.65)</td>
<td align="center" valign="middle">153 (49.35)</td>
<td align="center" valign="middle">174 (55.59)</td>
<td align="center" valign="middle">177 (56.37)</td>
<td align="center" valign="middle">173 (53.23)</td>
</tr>
<tr>
<td align="left" valign="middle">Missing</td>
<td align="center" valign="middle">216 (14.61)</td>
<td align="center" valign="middle">60 (16.22)</td>
<td align="center" valign="middle">55 (14.95)</td>
<td align="center" valign="middle">56 (15.14)</td>
<td align="center" valign="middle">45 (12.16)</td>
</tr>
<tr>
<td align="left" valign="middle">Cancer, <italic>n</italic> (%)</td>
<td align="center" valign="middle">222 (15.02)</td>
<td align="center" valign="middle">59 (15.95)</td>
<td align="center" valign="middle">49 (13.32)</td>
<td align="center" valign="middle">56 (15.14)</td>
<td align="center" valign="middle">58 (15.68)</td>
</tr>
<tr>
<td align="left" valign="middle">Missing</td>
<td align="center" valign="middle">3 (0.20)</td>
<td align="center" valign="middle">2 (0.54)</td>
<td align="center" valign="middle">0 (0.00)</td>
<td align="center" valign="middle">1 (0.27)</td>
<td align="center" valign="middle">0 (0.00)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="6">Major eye diseases</td>
</tr>
<tr>
<td align="left" valign="middle">Cataract</td>
<td align="center" valign="middle">230 (15.56)</td>
<td align="center" valign="middle">76 (20.54)</td>
<td align="center" valign="middle">63 (17.12)</td>
<td align="center" valign="middle">48 (12.97)</td>
<td align="center" valign="middle">43 (11.62)</td>
</tr>
<tr>
<td align="left" valign="middle">Glaucoma</td>
<td align="center" valign="middle">113 (7.65)</td>
<td align="center" valign="middle">35 (9.46)</td>
<td align="center" valign="middle">31 (8.42)</td>
<td align="center" valign="middle">22 (5.95)</td>
<td align="center" valign="middle">25 (6.76)</td>
</tr>
<tr>
<td align="left" valign="middle">Diabetic retinopathy</td>
<td align="center" valign="middle">94 (6.36)</td>
<td align="center" valign="middle">33 (8.92)</td>
<td align="center" valign="middle">29 (7.88)</td>
<td align="center" valign="middle">19 (5.14)</td>
<td align="center" valign="middle">13 (3.51)</td>
</tr>
<tr>
<td align="left" valign="middle">Age-related macular degeneration</td>
<td align="center" valign="middle">110 (7.44)</td>
<td align="center" valign="middle">32 (8.65)</td>
<td align="center" valign="middle">25 (6.79)</td>
<td align="center" valign="middle">25 (6.76)</td>
<td align="center" valign="middle">28 (7.57)</td>
</tr>
<tr>
<td align="left" valign="middle">Any ocular disease</td>
<td align="center" valign="middle">436 (29.50)</td>
<td align="center" valign="middle">131 (35.41)</td>
<td align="center" valign="middle">122 (33.15)</td>
<td align="center" valign="middle">97 (26.22)</td>
<td align="center" valign="middle">86 (23.24)</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec13">
<label>3.2</label>
<title>Association between serum carotenoid concentrations and risk of major age-related eye diseases</title>
<p>The association between serum carotenoid concentrations and risk of major eye diseases among middle-aged and older adults is presented in <xref ref-type="table" rid="tab2">Table 2</xref>. After multivariable adjustment, compared to participants in the first quartile (Q1), those in highest quartile (Q4) of serum <italic>&#x03B1;</italic>-carotene (OR: 0.37; 95% CI: 0.21&#x2013;0.64), <italic>&#x03B2;</italic>-carotene (OR: 0.57; 95% CI: 0.33&#x2013;0.95), and lutein/zeaxanthin (OR: 0.45; 95% CI: 0.27&#x2013;0.76) were negatively associated with risk of cataract; those in higher quartile (Q3) of serum <italic>&#x03B2;</italic>-cryptoxanthin (OR: 0.50; 95% CI: 0.27&#x2013;0.93) was negatively associated with risk of glaucoma; those in highest quartile of serum &#x03B2;-carotene (OR: 0.30; 95% CI: 0.11&#x2013;0.77) and &#x03B2;-cryptoxanthin (OR: 0.28; 95% CI: 0.12&#x2013;0.68) were negatively associated with risk of diabetic retinopathy; and those in highest quartile of lycopene (OR: 0.37; 95% CI: 0.180.78) was negatively associated with risk of AMD. In addition, the highest quartile of serum total carotenoid concentrations was negatively associated with risk of cataract (OR: 0.58; 95% CI: 0.35&#x2013;0.97) compared to the first quartile. Similar results were also observed in univariate analysis of the association between serum carotenoid concentrations and risk of major age-related eye diseases (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 2</xref>). Sensitivity analysis, which included additional adjustment for dietary carotenoid intake, showed that the association between serum carotenoids and the risk of age-related eye diseases remained largely unchanged (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 3</xref>). In addition, the sensitivity analysis to assess the possible effects of missing data yielded results was also conducted, and the results showed that these associations were robust across sensitivity analyses excluding participants with missing data on covariates (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 4</xref>).</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Association between serum carotenoid concentrations and risk of major age-related eye diseases among middle-aged and older adults.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Quartiles of serum carotenoids<break/>concentrations</th>
<th align="center" valign="top" colspan="2">Cataract</th>
<th align="center" valign="top" colspan="2">Glaucoma</th>
<th align="center" valign="top" colspan="2">Diabetic retinopathy</th>
<th align="center" valign="top" colspan="2">Age-related macular degeneration</th>
</tr>
<tr>
<th align="center" valign="top">Cases/controls</th>
<th align="center" valign="top">OR (95% CI)</th>
<th align="center" valign="top">Cases/controls</th>
<th align="center" valign="top">OR (95% CI)</th>
<th align="center" valign="top">Cases/controls</th>
<th align="center" valign="top">OR (95% CI)</th>
<th align="center" valign="top">Cases/controls</th>
<th align="center" valign="top">OR (95% CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" colspan="9">&#x03B1;-carotene (&#x03BC;mol/L)</td>
</tr>
<tr>
<td align="left" valign="top">Per 1-SD increase</td>
<td/>
<td align="center" valign="top">0.74 (0.58, 0.94)</td>
<td/>
<td align="center" valign="top">0.86 (0.64, 1.16)</td>
<td/>
<td align="center" valign="top">0.67 (0.40, 1.12)</td>
<td/>
<td align="center" valign="top">1.06 (0.85, 1.33)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 1</td>
<td align="char" valign="top" char="/">61/284</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">32/313</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">32/313</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">25/320</td>
<td align="center" valign="top">1.00 (Ref)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 2</td>
<td align="char" valign="top" char="/">59/324</td>
<td align="center" valign="top">0.62 (0.38, 1.00)</td>
<td align="char" valign="top" char="/">32/351</td>
<td align="center" valign="top">0.94 (0.54, 1.63)</td>
<td align="char" valign="top" char="/">32/351</td>
<td align="center" valign="top">1.24 (0.66, 2.35)</td>
<td align="char" valign="top" char="/">27/356</td>
<td align="center" valign="top">0.73 (0.40, 1.34)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 3</td>
<td align="char" valign="top" char="/">67/305</td>
<td align="center" valign="top">0.61 (0.37, 1.00)</td>
<td align="char" valign="top" char="/">30/342</td>
<td align="center" valign="top">0.77 (0.43, 1.37)</td>
<td align="char" valign="top" char="/">20/352</td>
<td align="center" valign="top">0.96 (0.46, 2.01)</td>
<td align="char" valign="top" char="/">30/342</td>
<td align="center" valign="top">0.70 (0.38, 1.30)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 4</td>
<td align="char" valign="top" char="/">43/335</td>
<td align="center" valign="top">0.37 (0.21, 0.64)</td>
<td align="char" valign="top" char="/">19/359</td>
<td align="center" valign="top">0.57 (0.29, 1.09)</td>
<td align="char" valign="top" char="/">10/368</td>
<td align="center" valign="top">0.43 (0.18, 1.05)</td>
<td align="char" valign="top" char="/">28/350</td>
<td align="center" valign="top">0.67 (0.35, 1.28)</td>
</tr>
<tr>
<td align="left" valign="top"><italic>P</italic> for trend</td>
<td/>
<td align="center" valign="top">&#x003C;0.001</td>
<td/>
<td align="center" valign="top">0.072</td>
<td/>
<td align="center" valign="top">0.091</td>
<td/>
<td align="center" valign="top">0.263</td>
</tr>
<tr>
<td align="left" valign="top" colspan="9">&#x03B2;-carotene (&#x03BC;mol/L)</td>
</tr>
<tr>
<td align="left" valign="top">Per 1-SD increase</td>
<td/>
<td align="center" valign="top">0.95 (0.80, 1.12)</td>
<td/>
<td align="center" valign="top">0.90 (0.70, 1.17)</td>
<td/>
<td align="center" valign="top">0.39 (0.20, 0.78)</td>
<td/>
<td align="center" valign="top">1.18 (1.01, 1.38)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 1</td>
<td align="char" valign="top" char="/">55/309</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">29/335</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">37/327</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">20/344</td>
<td align="center" valign="top">1.00 (Ref)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 2</td>
<td align="char" valign="top" char="/">52/323</td>
<td align="center" valign="top">0.62 (0.38, 1.03)</td>
<td align="char" valign="top" char="/">30/345</td>
<td align="center" valign="top">0.83 (0.47, 1.45)</td>
<td align="char" valign="top" char="/">30/345</td>
<td align="center" valign="top">1.14 (0.61, 2.12)</td>
<td align="char" valign="top" char="/">34/341</td>
<td align="center" valign="top">1.44 (0.78, 2.67)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 3</td>
<td align="char" valign="top" char="/">60/309</td>
<td align="center" valign="top">0.64 (0.39, 1.06)</td>
<td align="char" valign="top" char="/">23/346</td>
<td align="center" valign="top">0.57 (0.31, 1.05)</td>
<td align="char" valign="top" char="/">19/350</td>
<td align="center" valign="top">0.85 (0.42, 1.75)</td>
<td align="char" valign="top" char="/">18/351</td>
<td align="center" valign="top">0.56 (0.28, 1.14)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 4</td>
<td align="char" valign="top" char="/">63/307</td>
<td align="center" valign="top">0.57 (0.33, 0.95)</td>
<td align="char" valign="top" char="/">31/339</td>
<td align="center" valign="top">0.77 (0.42, 1.40)</td>
<td align="char" valign="top" char="/">8/362</td>
<td align="center" valign="top">0.30 (0.11, 0.77)</td>
<td align="char" valign="top" char="/">38/332</td>
<td align="center" valign="top">1.29 (0.68, 2.48)</td>
</tr>
<tr>
<td align="left" valign="top"><italic>P</italic> for trend</td>
<td/>
<td align="center" valign="top">0.057</td>
<td/>
<td align="center" valign="top">0.269</td>
<td/>
<td align="center" valign="top">0.028</td>
<td/>
<td align="center" valign="top">0.960</td>
</tr>
<tr>
<td align="left" valign="top" colspan="9">&#x03B2;-cryptoxanthin (&#x03BC;mol/L)</td>
</tr>
<tr>
<td align="left" valign="top">Per 1-SD increase</td>
<td/>
<td align="center" valign="top">0.88 (0.70, 1.10)</td>
<td/>
<td align="center" valign="top">1.02 (0.82, 1.28)</td>
<td/>
<td align="center" valign="top">0.56 (0.37, 0.86)</td>
<td/>
<td align="center" valign="top">0.83 (0.61, 1.12)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 1</td>
<td align="char" valign="top" char="/">61/309</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">35/335</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">32/338</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">28/342</td>
<td align="center" valign="top">1.00 (Ref)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 2</td>
<td align="char" valign="top" char="/">60/308</td>
<td align="center" valign="top">1.08 (0.67, 1.72)</td>
<td align="char" valign="top" char="/">28/340</td>
<td align="center" valign="top">0.76 (0.44, 1.31)</td>
<td align="char" valign="top" char="/">32/336</td>
<td align="center" valign="top">0.98 (0.52, 1.87)</td>
<td align="char" valign="top" char="/">22/346</td>
<td align="center" valign="top">0.80 (0.43, 1.47)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 3</td>
<td align="char" valign="top" char="/">63/307</td>
<td align="center" valign="top">1.13 (0.70, 1.83)</td>
<td align="char" valign="top" char="/">19/351</td>
<td align="center" valign="top">0.50 (0.27, 0.93)</td>
<td align="char" valign="top" char="/">17/353</td>
<td align="center" valign="top">0.61 (0.29, 1.31)</td>
<td align="char" valign="top" char="/">39/331</td>
<td align="center" valign="top">1.34 (0.76, 2.35)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 4</td>
<td align="char" valign="top" char="/">46/324</td>
<td align="center" valign="top">0.69 (0.41, 1.16)</td>
<td align="char" valign="top" char="/">31/339</td>
<td align="center" valign="top">0.88 (0.49, 1.55)</td>
<td align="char" valign="top" char="/">13/357</td>
<td align="center" valign="top">0.28 (0.12, 0.68)</td>
<td align="char" valign="top" char="/">21/349</td>
<td align="center" valign="top">0.68 (0.36, 1.31)</td>
</tr>
<tr>
<td align="left" valign="top"><italic>P</italic> for trend</td>
<td/>
<td align="center" valign="top">0.236</td>
<td/>
<td align="center" valign="top">0.415</td>
<td/>
<td align="center" valign="top">0.004</td>
<td/>
<td align="center" valign="top">0.620</td>
</tr>
<tr>
<td align="left" valign="top" colspan="9">Lycopene (&#x03BC;mol/L)</td>
</tr>
<tr>
<td align="left" valign="top">Per 1-SD increase</td>
<td/>
<td align="center" valign="top">0.99 (0.81, 1.21)</td>
<td/>
<td align="center" valign="top">0.94 (0.76, 1.18)</td>
<td/>
<td align="center" valign="top">0.99 (0.76, 1.30)</td>
<td/>
<td align="center" valign="top">0.74 (0.57, 0.95)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 1</td>
<td align="char" valign="top" char="/">83/286</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">41/328</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">29/340</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">35/334</td>
<td align="center" valign="top">1.00 (Ref)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 2</td>
<td align="char" valign="top" char="/">62/307</td>
<td align="center" valign="top">0.83 (0.54, 1.28)</td>
<td align="char" valign="top" char="/">26/343</td>
<td align="center" valign="top">0.62 (0.36, 1.06)</td>
<td align="char" valign="top" char="/">22/347</td>
<td align="center" valign="top">0.90 (0.45, 1.80)</td>
<td align="char" valign="top" char="/">35/334</td>
<td align="center" valign="top">1.08 (0.64, 1.83)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 3</td>
<td align="char" valign="top" char="/">50/320</td>
<td align="center" valign="top">0.97 (0.61, 1.55)</td>
<td align="char" valign="top" char="/">25/345</td>
<td align="center" valign="top">0.67 (0.39, 1.17)</td>
<td align="char" valign="top" char="/">25/345</td>
<td align="center" valign="top">1.14 (0.57, 2.26)</td>
<td align="char" valign="top" char="/">29/341</td>
<td align="center" valign="top">0.96 (0.54, 1.69)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 4</td>
<td align="char" valign="top" char="/">35/335</td>
<td align="center" valign="top">0.83 (0.50, 1.39)</td>
<td align="char" valign="top" char="/">21/349</td>
<td align="center" valign="top">0.66 (0.37, 1.20)</td>
<td align="char" valign="top" char="/">18/352</td>
<td align="center" valign="top">0.99 (0.47, 2.08)</td>
<td align="char" valign="top" char="/">11/359</td>
<td align="center" valign="top">0.37 (0.18, 0.78)</td>
</tr>
<tr>
<td align="left" valign="top"><italic>P</italic> for trend</td>
<td/>
<td align="center" valign="top">0.605</td>
<td/>
<td align="center" valign="top">0.163</td>
<td/>
<td align="center" valign="top">0.857</td>
<td/>
<td align="center" valign="top">0.019</td>
</tr>
<tr>
<td align="left" valign="top" colspan="9">Lutein/zeaxanthin (&#x03BC;mol/L)</td>
</tr>
<tr>
<td align="left" valign="top">Per 1-SD increase</td>
<td/>
<td align="center" valign="top">0.81 (0.67, 0.98)</td>
<td/>
<td align="center" valign="top">0.97 (0.78, 1.21)</td>
<td/>
<td align="center" valign="top">1.04 (0.81, 1.32)</td>
<td/>
<td align="center" valign="top">1.29 (1.08, 1.55)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 1</td>
<td align="char" valign="top" char="/">71/299</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">25/345</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">32/338</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">25/345</td>
<td align="center" valign="top">1.00 (Ref)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 2</td>
<td align="char" valign="top" char="/">65/298</td>
<td align="center" valign="top">0.91 (0.58, 1.45)</td>
<td align="char" valign="top" char="/">26/337</td>
<td align="center" valign="top">1.03 (0.57, 1.86)</td>
<td align="char" valign="top" char="/">21/342</td>
<td align="center" valign="top">0.64 (0.31, 1.31)</td>
<td align="char" valign="top" char="/">32/331</td>
<td align="center" valign="top">1.27 (0.71, 2.29)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 3</td>
<td align="char" valign="top" char="/">59/313</td>
<td align="center" valign="top">0.81 (0.50, 1.30)</td>
<td align="char" valign="top" char="/">37/335</td>
<td align="center" valign="top">1.41 (0.79, 2.50)</td>
<td align="char" valign="top" char="/">20/352</td>
<td align="center" valign="top">0.76 (0.37, 1.60)</td>
<td align="char" valign="top" char="/">28/344</td>
<td align="center" valign="top">1.16 (0.63, 2.13)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 4</td>
<td align="char" valign="top" char="/">35/338</td>
<td align="center" valign="top">0.45 (0.27, 0.76)</td>
<td align="char" valign="top" char="/">25/348</td>
<td align="center" valign="top">0.95 (0.51, 1.76)</td>
<td align="char" valign="top" char="/">21/352</td>
<td align="center" valign="top">0.64 (0.31, 1.34)</td>
<td align="char" valign="top" char="/">25/348</td>
<td align="center" valign="top">1.09 (0.58, 2.05)</td>
</tr>
<tr>
<td align="left" valign="top"><italic>P</italic> for trend</td>
<td/>
<td align="center" valign="top">0.004</td>
<td/>
<td align="center" valign="top">0.860</td>
<td/>
<td align="center" valign="top">0.326</td>
<td/>
<td align="center" valign="top">0.893</td>
</tr>
<tr>
<td align="left" valign="top" colspan="9">Total carotenoid (&#x03BC;mol/L)</td>
</tr>
<tr>
<td align="left" valign="top">Per 1-SD increase</td>
<td/>
<td align="center" valign="top">0.88 (0.73, 1.07)</td>
<td/>
<td align="center" valign="top">0.91 (0.72, 1.16)</td>
<td/>
<td align="center" valign="top">0.73 (0.51, 1.05)</td>
<td/>
<td align="center" valign="top">1.10 (0.90, 1.35)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 1</td>
<td align="char" valign="top" char="/">76/294</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">35/335</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">33/337</td>
<td align="center" valign="top">1.00 (Ref)</td>
<td align="char" valign="top" char="/">32/338</td>
<td align="center" valign="top">1.00 (Ref)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 2</td>
<td align="char" valign="top" char="/">63/305</td>
<td align="center" valign="top">0.98 (0.62, 1.53)</td>
<td align="char" valign="top" char="/">31/337</td>
<td align="center" valign="top">0.85 (0.50, 1.47)</td>
<td align="char" valign="top" char="/">29/339</td>
<td align="center" valign="top">1.08 (0.56, 2.08)</td>
<td align="char" valign="top" char="/">25/343</td>
<td align="center" valign="top">0.81 (0.45, 1.45)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 3</td>
<td align="char" valign="top" char="/">48/322</td>
<td align="center" valign="top">0.59 (0.37, 0.96)</td>
<td align="char" valign="top" char="/">22/348</td>
<td align="center" valign="top">0.58 (0.32, 1.05)</td>
<td align="char" valign="top" char="/">19/351</td>
<td align="center" valign="top">1.07 (0.52, 2.19)</td>
<td align="char" valign="top" char="/">25/345</td>
<td align="center" valign="top">0.71 (0.39, 1.28)</td>
</tr>
<tr>
<td align="left" valign="top">Quartile 4</td>
<td align="char" valign="top" char="/">43/327</td>
<td align="center" valign="top">0.58 (0.35, 0.97)</td>
<td align="char" valign="top" char="/">25/345</td>
<td align="center" valign="top">0.77 (0.43, 1.40)</td>
<td align="char" valign="top" char="/">13/357</td>
<td align="center" valign="top">0.54 (0.24, 1.22)</td>
<td align="char" valign="top" char="/">28/342</td>
<td align="center" valign="top">0.87 (0.48, 1.59)</td>
</tr>
<tr>
<td align="left" valign="top"><italic>P</italic> for trend</td>
<td/>
<td align="center" valign="top">0.010</td>
<td/>
<td align="center" valign="top">0.211</td>
<td/>
<td align="center" valign="top">0.214</td>
<td/>
<td align="center" valign="top">0.569</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>P for trend was obtained by including the quartile number as a continuous variable in the regression model. Models were adjusted for age (continuous), sex (male or female), race/ethnicity (non-Hispanic white, black, Mexican-American, other Hispanic, or other race/ethnicity), education level (less than high school, high school or equivalent, or college or above), family income-to-poverty ratio (&#x003C;1.3, 1.3 to &#x2264;3.5, &#x003E;3.5, or missing), body mass index (&#x003C;18.5, 18.5 to &#x003C;25, 25 to &#x003C;30, &#x2265;30&#x202F;kg/m<sup>2</sup>, or missing), drinking status (non-drinker or drinker), smoking status (never smoker, former smoker, current smoker, or missing), HbA1c (&#x003C;6.5%, &#x2265;6.5%, or missing), hypertension (yes, no, or missing), hypercholesterolemia (yes, no, or missing), and cancer (yes, no, or missing).</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec14">
<label>3.3</label>
<title>Association between serum carotenoid concentrations and risk of any ocular disease among middle-aged and older adults</title>
<p>As shown in <xref ref-type="fig" rid="fig1">Figure 1</xref>, the restricted cubic spline results showed that the negative dose&#x2013;response association between serum <italic>&#x03B1;</italic>-carotene, <italic>&#x03B2;</italic>-carotene, &#x03B2;-cryptoxanthin, lycopene, lutein/zeaxanthin, and total carotenoid concentrations and risk of any ocular disease among middle-aged and older adults. In addition, multivariable adjustment model results showed that compared to participants in the first quartile, those in highest quartile of serum <italic>&#x03B1;</italic>-carotene (OR: 0.47; 95% CI: 0.31&#x2013;0.71), <italic>&#x03B2;</italic>-carotene (OR: 0.54; 95% CI: 0.36&#x2013;0.81), &#x03B2;-cryptoxanthin (OR: 0.67; 95% CI: 0.45&#x2013;0.99), lycopene (OR: 0.62; 95% CI: 0.42&#x2013;0.91), and total carotenoid (OR: 0.63; 95% CI: 0.42&#x2013;0.92) concentrations were negatively associated with risk of any ocular disease (<xref ref-type="table" rid="tab3">Table 3</xref>). The associations between serum carotenoid concentrations and risk of any ocular disease were also robust across sensitivity analyses excluding participants with missing data on covariates (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 5</xref>).</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Dose&#x2013;response association between geriatric nutritional risk index and cognitive function level among older adults with cardiometabolic disease. <bold>(A)</bold> &#x03B1;-carotene; <bold>(B)</bold> &#x03B2;-carotene; <bold>(C)</bold> &#x03B2;-cryptoxanthin; <bold>(D)</bold> lycopene; <bold>(E)</bold> lutein/zeaxanthin; <bold>(F)</bold> total carotenoid.</p>
</caption>
<graphic xlink:href="fmed-12-1596799-g001.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Graphs A to F display the relationship between carotenoid concentrations and ocular disease risk. Each graph illustrates odds ratio (OR) curves with 95% confidence intervals. (A) Serum alpha-carotene, (B) beta-carotene, (C) beta-cryptoxanthin, (D) lycopene, (E) lutein/zeaxanthin, and (F) total carotenoids. Generally, higher carotenoid levels are associated with lower risk. The confidence intervals, shaded in blue, show variability around each trend line. All graphs have x-axis labeled with specific carotenoid concentrations in micromoles per liter and y-axis labeled with OR for risk of any ocular disease.</alt-text>
</graphic>
</fig>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Association between serum carotenoid concentrations and risk of ocular disease among middle-aged and older adults.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th rowspan="3"/>
<th align="center" valign="top" colspan="4">Quartiles of serum carotenoid concentrations (&#x03BC;mol/L)</th>
<th align="center" valign="top" rowspan="3">Per 1-SD increase</th>
<th align="center" valign="top" rowspan="3"><italic>P</italic> for trend</th>
</tr>
<tr>
<th align="center" valign="top">Quartile 1</th>
<th align="center" valign="top">Quartile 2</th>
<th align="center" valign="top">Quartile 3</th>
<th align="center" valign="top">Quartile 4</th>
</tr>
<tr>
<th align="center" valign="top">OR (95% CI)</th>
<th align="center" valign="top">OR (95% CI)</th>
<th align="center" valign="top">OR (95% CI)</th>
<th align="center" valign="top">OR (95% CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" colspan="7">&#x03B1;-carotene</td>
</tr>
<tr>
<td align="left" valign="middle">Cases/controls</td>
<td align="center" valign="middle">112/233</td>
<td align="center" valign="middle">126/257</td>
<td align="center" valign="middle">115/257</td>
<td align="center" valign="middle">83/295</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Crude model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">1.02 (0.75, 1.39)</td>
<td align="center" valign="middle">0.93 (0.68, 1.28)</td>
<td align="center" valign="middle">0.59 (0.42, 0.82)</td>
<td align="char" valign="middle" char="(">0.85 (0.74, 0.97)</td>
<td align="char" valign="middle" char=".">0.002</td>
</tr>
<tr>
<td align="left" valign="middle">Multivariate model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">0.96 (0.67, 1.38)</td>
<td align="center" valign="middle">0.73 (0.50, 1.08)</td>
<td align="center" valign="middle">0.47 (0.31, 0.71)</td>
<td align="char" valign="middle" char="(">0.81 (0.68, 0.97)</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">&#x03B2;-carotene</td>
</tr>
<tr>
<td align="left" valign="middle">Cases/controls</td>
<td align="center" valign="middle">116/248</td>
<td align="center" valign="middle">115/260</td>
<td align="center" valign="middle">100/269</td>
<td align="center" valign="middle">105/265</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Crude model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">0.95 (0.69, 1.29)</td>
<td align="center" valign="middle">0.79 (0.58, 1.09)</td>
<td align="center" valign="middle">0.85 (0.62, 1.16)</td>
<td align="char" valign="middle" char="(">1.02 (0.92, 1.14)</td>
<td align="char" valign="middle" char=".">0.188</td>
</tr>
<tr>
<td align="left" valign="middle">Multivariate model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">0.81 (0.56, 1.16)</td>
<td align="center" valign="middle">0.54 (0.37, 0.80)</td>
<td align="center" valign="middle">0.54 (0.36, 0.81)</td>
<td align="char" valign="middle" char="(">0.96 (0.84, 1.09)</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7"><italic>&#x03B2;</italic>-cryptoxanthin</td>
</tr>
<tr>
<td align="left" valign="middle">Cases/controls</td>
<td align="center" valign="middle">118/252</td>
<td align="center" valign="middle">111/257</td>
<td align="center" valign="middle">115/255</td>
<td align="center" valign="middle">92/278</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Crude model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">0.92 (0.68, 1.26)</td>
<td align="center" valign="middle">0.96 (0.71, 1.31)</td>
<td align="center" valign="middle">0.71 (0.51, 0.97)</td>
<td align="char" valign="middle" char="(">0.89 (0.78, 1.01)</td>
<td align="char" valign="middle" char=".">0.057</td>
</tr>
<tr>
<td align="left" valign="middle">Multivariate model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">0.94 (0.66, 1.35)</td>
<td align="center" valign="middle">1.02 (0.70, 1.48)</td>
<td align="center" valign="middle">0.67 (0.45, 0.99)</td>
<td align="char" valign="middle" char="(">0.90 (0.77, 1.06)</td>
<td align="char" valign="middle" char=".">0.085</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">Lycopene</td>
</tr>
<tr>
<td align="left" valign="middle">Cases/controls</td>
<td align="center" valign="middle">143/226</td>
<td align="center" valign="middle">113/256</td>
<td align="center" valign="middle">110/260</td>
<td align="center" valign="middle">70/300</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Crude model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">0.70 (0.51, 0.95)</td>
<td align="center" valign="middle">0.67 (0.49, 0.91)</td>
<td align="center" valign="middle">0.37 (0.26, 0.51)</td>
<td align="char" valign="middle" char="(">0.70 (0.62, 0.80)</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Multivariate model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">0.80 (0.56, 1.13)</td>
<td align="center" valign="middle">0.98 (0.69, 1.39)</td>
<td align="center" valign="middle">0.62 (0.42, 0.91)</td>
<td align="char" valign="middle" char="(">0.90 (0.78, 1.04)</td>
<td align="char" valign="middle" char=".">0.057</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">Lutein/zeaxanthin</td>
</tr>
<tr>
<td align="left" valign="middle">Cases/controls</td>
<td align="center" valign="middle">115/255</td>
<td align="center" valign="middle">114/249</td>
<td align="center" valign="middle">118/254</td>
<td align="center" valign="middle">89/284</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Crude model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">1.01 (0.74, 1.38)</td>
<td align="center" valign="middle">1.04 (0.76, 1.42)</td>
<td align="center" valign="middle">0.69 (0.50, 0.96)</td>
<td align="char" valign="middle" char="(">0.99 (0.89, 1.11)</td>
<td align="char" valign="middle" char=".">0.046</td>
</tr>
<tr>
<td align="left" valign="middle">Multivariate model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">0.99 (0.69, 1.43)</td>
<td align="center" valign="middle">1.06 (0.73, 1.54)</td>
<td align="center" valign="middle">0.69 (0.47, 1.01)</td>
<td align="char" valign="middle" char="(">1.01 (0.88, 1.15)</td>
<td align="char" valign="middle" char=".">0.086</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="7">Total carotenoid</td>
</tr>
<tr>
<td align="left" valign="middle">Cases/controls</td>
<td align="center" valign="middle">131/239</td>
<td align="center" valign="middle">122/246</td>
<td align="center" valign="middle">97/273</td>
<td align="center" valign="middle">86/284</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Crude model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">0.90 (0.67, 1.23)</td>
<td align="center" valign="middle">0.65 (0.47, 0.89)</td>
<td align="center" valign="middle">0.55 (0.40, 0.76)</td>
<td align="char" valign="middle" char="(">0.86 (0.76, 0.97)</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Multivariate model</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="center" valign="middle">1.05 (0.73, 1.49)</td>
<td align="center" valign="middle">0.70 (0.49, 1.02)</td>
<td align="center" valign="middle">0.63 (0.42, 0.92)</td>
<td align="char" valign="middle" char="(">0.91 (0.78, 1.04)</td>
<td align="char" valign="middle" char=".">0.004</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>P for trend was obtained by including the quartile number as a continuous variable in the regression model. Models were adjusted for age (continuous), sex (male or female), race/ethnicity (non-Hispanic white, black, Mexican-American, other Hispanic, or other race/ethnicity), education level (less than high school, high school or equivalent, college or above, or missing), family income-to-poverty ratio (&#x003C;1.3, 1.3 to &#x2264;3.5, &#x003E;3.5, or missing), body mass index (&#x003C;18.5, 18.5 to &#x003C;25, 25 to &#x003C;30, &#x2265;30&#x202F;kg/m2, or missing), drinking status (non-drinker or drinker), smoking status (never smoker, former smoker, current smoker, or missing), HbA1c (&#x003C;6.5%, &#x2265;6.5%, or missing), hypertension (yes, no, or missing), hypercholesterolemia (yes, no, or missing), and cancer (yes, no, or missing).</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec15">
<label>3.4</label>
<title>Subgroup analysis</title>
<p>Subgroup analysis stratified by sex was conducted to examine the association between serum carotenoid concentrations and risk of any ocular disease (<xref ref-type="table" rid="tab4">Table 4</xref>). Compared to participants in the first quartile, those in highest quartile of serum <italic>&#x03B1;</italic>-carotene (OR: 0.16; 95% CI: 0.08&#x2013;0.31), <italic>&#x03B2;</italic>-carotene (OR: 0.39; 95% CI: 0.21&#x2013;0.75), &#x03B2;-cryptoxanthin (OR: 0.46; 95% CI: 0.24&#x2013;0.87), lycopene (OR: 0.45; 95% CI: 0.24&#x2013;0.83), lutein/zeaxanthin (OR: 0.43; 95% CI: 0.23&#x2013;0.78), and total carotenoid (OR: 0.41; 95% CI: 0.22&#x2013;0.76) concentrations were negatively associated with risk of any ocular disease among female participants. By contrast, no association was observed between serum total carotenoid concentrations and risk of any ocular disease among male participants (all <italic>P</italic> for trend&#x003E;0.05).</p>
<table-wrap position="float" id="tab4">
<label>Table 4</label>
<caption>
<p>Association between serum carotenoid concentrations and risk of ocular disease among middle-aged and older adults by sex.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Quartiles of serum carotenoid concentrations</th>
<th align="center" valign="top" colspan="2">Male</th>
<th align="center" valign="top" colspan="2">Female</th>
<th align="center" valign="top" rowspan="2"><italic>P</italic> for interaction</th>
</tr>
<tr>
<th align="center" valign="top">Cases/controls</th>
<th align="center" valign="top">OR (95% CI)</th>
<th align="center" valign="top">Cases/controls</th>
<th align="center" valign="top">OR (95% CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">&#x03B1;-carotene</td>
<td/>
<td/>
<td/>
<td/>
<td align="char" valign="middle" char=".">&#x003C; 0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Per 1-SD increase</td>
<td/>
<td align="center" valign="middle">1.09 (0.88, 1.35)</td>
<td/>
<td align="center" valign="middle">0.59 (0.44, 0.79)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 1</td>
<td align="char" valign="middle" char="/">59/156</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="char" valign="middle" char="/">53/77</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 2</td>
<td align="char" valign="middle" char="/">75/136</td>
<td align="center" valign="middle">1.47 (0.91, 2.36)</td>
<td align="char" valign="middle" char="/">51/121</td>
<td align="center" valign="middle">0.45 (0.25, 0.84)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 3</td>
<td align="char" valign="middle" char="/">53/137</td>
<td align="center" valign="middle">0.85 (0.51, 1.43)</td>
<td align="char" valign="middle" char="/">62/120</td>
<td align="center" valign="middle">0.46 (0.25, 0.86)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 4</td>
<td align="char" valign="middle" char="/">44/115</td>
<td align="center" valign="middle">1.01 (0.58, 1.74)</td>
<td align="char" valign="middle" char="/">39/180</td>
<td align="center" valign="middle">0.16 (0.08, 0.31)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle"><italic>P</italic> for trend</td>
<td/>
<td align="center" valign="middle">0.518</td>
<td/>
<td align="center" valign="middle">&#x003C;0.001</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">&#x03B2;-carotene</td>
<td/>
<td/>
<td/>
<td/>
<td align="char" valign="middle" char=".">0.318</td>
</tr>
<tr>
<td align="left" valign="middle">Per 1-SD increase</td>
<td/>
<td align="center" valign="middle">1.05 (0.84, 1.32)</td>
<td/>
<td align="center" valign="middle">0.91 (0.76, 1.08)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 1</td>
<td align="char" valign="middle" char="/">75/166</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="char" valign="middle" char="/">41/82</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 2</td>
<td align="char" valign="middle" char="/">64/139</td>
<td align="center" valign="middle">0.93 (0.58, 1.48)</td>
<td align="char" valign="middle" char="/">51/121</td>
<td align="center" valign="middle">0.58 (0.31, 1.08)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 3</td>
<td align="char" valign="middle" char="/">51/142</td>
<td align="center" valign="middle">0.61 (0.37, 0.99)</td>
<td align="char" valign="middle" char="/">49/127</td>
<td align="center" valign="middle">0.39 (0.20, 0.74)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 4</td>
<td align="char" valign="middle" char="/">41/97</td>
<td align="center" valign="middle">0.66 (0.38, 1.13)</td>
<td align="char" valign="middle" char="/">64/168</td>
<td align="center" valign="middle">0.39 (0.21, 0.75)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">P for trend</td>
<td/>
<td align="center" valign="middle">0.044</td>
<td/>
<td align="center" valign="middle">&#x003C;0.001</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">&#x03B2;-cryptoxanthin</td>
<td/>
<td/>
<td/>
<td/>
<td align="char" valign="middle" char=".">0.028</td>
</tr>
<tr>
<td align="left" valign="middle">Per 1-SD increase</td>
<td/>
<td align="center" valign="middle">1.05 (0.88, 1.27)</td>
<td/>
<td align="center" valign="middle">0.73 (0.56, 0.96)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 1</td>
<td align="char" valign="middle" char="/">65/152</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="char" valign="middle" char="/">53/100</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 2</td>
<td align="char" valign="middle" char="/">57/136</td>
<td align="center" valign="middle">0.94 (0.58, 1.52)</td>
<td align="char" valign="middle" char="/">54/121</td>
<td align="center" valign="middle">0.90 (0.50, 1.60)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 3</td>
<td align="char" valign="middle" char="/">62/129</td>
<td align="center" valign="middle">1.08 (0.66, 1.75)</td>
<td align="char" valign="middle" char="/">53/126</td>
<td align="center" valign="middle">0.95 (0.52, 1.74)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 4</td>
<td align="char" valign="middle" char="/">47/127</td>
<td align="center" valign="middle">0.90 (0.53, 1.51)</td>
<td align="char" valign="middle" char="/">45/151</td>
<td align="center" valign="middle">0.46 (0.24, 0.87)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle"><italic>P</italic> for trend</td>
<td/>
<td align="center" valign="middle">0.843</td>
<td/>
<td align="center" valign="middle">0.025</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Lycopene</td>
<td/>
<td/>
<td/>
<td/>
<td align="char" valign="middle" char=".">0.086</td>
</tr>
<tr>
<td align="left" valign="middle">Per 1-SD increase</td>
<td/>
<td align="center" valign="middle">1.01 (0.84, 1.22)</td>
<td/>
<td align="center" valign="middle">0.78 (0.61, 0.99)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 1</td>
<td align="char" valign="middle" char="/">69/130</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="char" valign="middle" char="/">74/96</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 2</td>
<td align="char" valign="middle" char="/">57/126</td>
<td align="center" valign="middle">0.92 (0.57, 1.49)</td>
<td align="char" valign="middle" char="/">56/130</td>
<td align="center" valign="middle">0.70 (0.41, 1.18)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 3</td>
<td align="char" valign="middle" char="/">63/133</td>
<td align="center" valign="middle">1.28 (0.79, 2.09)</td>
<td align="char" valign="middle" char="/">47/127</td>
<td align="center" valign="middle">0.71 (0.41, 1.23)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 4</td>
<td align="char" valign="middle" char="/">42/155</td>
<td align="center" valign="middle">0.88 (0.52, 1.48)</td>
<td align="char" valign="middle" char="/">28/145</td>
<td align="center" valign="middle">0.45 (0.24, 0.83)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle"><italic>P</italic> for trend</td>
<td/>
<td align="center" valign="middle">0.981</td>
<td/>
<td align="center" valign="middle">0.017</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Lutein/zeaxanthin</td>
<td/>
<td/>
<td/>
<td/>
<td align="char" valign="middle" char=".">0.008</td>
</tr>
<tr>
<td align="left" valign="middle">Per 1-SD increase</td>
<td/>
<td align="center" valign="middle">1.15 (0.98, 1.36)</td>
<td/>
<td align="center" valign="middle">0.79 (0.63, 0.99)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 1</td>
<td align="char" valign="middle" char="/">56/138</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="char" valign="middle" char="/">59/117</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 2</td>
<td align="char" valign="middle" char="/">61/144</td>
<td align="center" valign="middle">1.04 (0.63, 1.73)</td>
<td align="char" valign="middle" char="/">54/109</td>
<td align="center" valign="middle">0.80 (0.45, 1.44)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 3</td>
<td align="char" valign="middle" char="/">65/128</td>
<td align="center" valign="middle">1.34 (0.81, 2.21)</td>
<td align="char" valign="middle" char="/">52/122</td>
<td align="center" valign="middle">0.70 (0.39, 1.26)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 4</td>
<td align="char" valign="middle" char="/">49/134</td>
<td align="center" valign="middle">0.91 (0.54, 1.53)</td>
<td align="char" valign="middle" char="/">40/150</td>
<td align="center" valign="middle">0.43 (0.23, 0.78)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle"><italic>P</italic> for trend</td>
<td/>
<td align="center" valign="middle">0.974</td>
<td/>
<td align="center" valign="middle">0.006</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Total carotenoid</td>
<td/>
<td/>
<td/>
<td/>
<td align="char" valign="middle" char=".">0.015</td>
</tr>
<tr>
<td align="left" valign="middle">Per 1-SD increase</td>
<td/>
<td align="center" valign="middle">1.09 (0.89, 1.33)</td>
<td/>
<td align="center" valign="middle">0.75 (0.60, 0.94)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 1</td>
<td align="char" valign="middle" char="/">75/144</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td align="char" valign="middle" char="/">56/95</td>
<td align="center" valign="middle">1.00 (Ref)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 2</td>
<td align="char" valign="middle" char="/">60/133</td>
<td align="center" valign="middle">0.93 (0.58, 1.49)</td>
<td align="char" valign="middle" char="/">62/113</td>
<td align="center" valign="middle">1.13 (0.64, 1.98)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 3</td>
<td align="char" valign="middle" char="/">51/147</td>
<td align="center" valign="middle">0.76 (0.47, 1.23)</td>
<td align="char" valign="middle" char="/">46/126</td>
<td align="center" valign="middle">0.55 (0.30, 1.00)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Quartile 4</td>
<td align="char" valign="middle" char="/">45/120</td>
<td align="center" valign="middle">0.90 (0.53, 1.51)</td>
<td align="char" valign="middle" char="/">41/164</td>
<td align="center" valign="middle">0.41 (0.22, 0.76)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle"><italic>P</italic> for trend</td>
<td/>
<td align="center" valign="top">0.484</td>
<td/>
<td align="center" valign="top">&#x003C;0.001</td>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>P for trend was obtained by including the quartile number as a continuous variable in the regression model. P for interaction was calculated using the likelihood ratio test. Models were adjusted for age (continuous), race/ethnicity (non-Hispanic white, black, Mexican-American, other Hispanic, or other race/ethnicity), education level (less than high school, high school or equivalent, college or above, or missing), family income-to-poverty ratio (&#x003C;1.3, 1.3 to &#x2264;3.5, &#x003E;3.5, or missing), body mass index (&#x003C;18.5, 18.5 to &#x003C;25, 25 to &#x003C;30, &#x2265;30&#x202F;kg/m2, or missing), drinking status (non-drinker or drinker), smoking status (never smoker, former smoker, current smoker, or missing), HbA1c (&#x003C;6.5%, &#x2265;6.5%, or missing), hypertension (yes, no, or missing), hypercholesterolemia (yes, no, or missing), and cancer (yes, no, or missing).</p>
</table-wrap-foot>
</table-wrap>
<p>Furthermore, compared to those in the first quartile, the highest quartile of serum <italic>&#x03B1;</italic>-carotene (OR: 0.15; 95% CI: 0.06&#x2013;0.36), <italic>&#x03B2;</italic>-carotene (OR: 0.42; 95% CI: 0.18&#x2013;0.97), lutein/zeaxanthin (OR: 0.26; 95% CI: 0.11&#x2013;0.61), and total carotenoid (OR: 0.35; 95% CI: 0.15&#x2013;0.80) concentrations were negatively associated with risk of cataract among female participants (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 6</xref>); the highest quartile of serum <italic>&#x03B1;</italic>-carotene (OR: 0.24; 95% CI: 0.09&#x2013;0.67) was negatively associated with risk of glaucoma among female participants (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 7</xref>); those in highest quartile of serum &#x03B1;-carotene (OR: 0.22; 95% CI: 0.06&#x2013;0.82) and <italic>&#x03B2;</italic>-carotene (OR: 0.24; 95% CI: 0.06&#x2013;0.95) were negatively associated with risk of diabetic retinopathy among female participants; those in highest quartile of serum &#x03B2;-cryptoxanthin (OR: 0.25; 95% CI: 0.07&#x2013;0.88) was also negatively associated with risk of diabetic retinopathy among male participants (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 8</xref>); and those in the highest quartile of serum lycopene (OR: 0.14; 95% CI: 0.03, 0.67) was negatively associated with risk of AMD among female participants (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 9</xref>). In addition, we performed stratified analyses by smoking status, and did not find a statistically significant interaction between smoking status and <italic>&#x03B2;</italic>-carotene, &#x03B2;-cryptoxanthin, lutein/zeaxanthin, lycopene, and total carotenoid levels on the risk of age-related ocular diseases in our analysis (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 10</xref>).</p>
</sec>
</sec>
<sec sec-type="discussion" id="sec16">
<label>4</label>
<title>Discussion</title>
<p>The present study investigated the associations between the serum carotenoid concentration and the risk of major age-related eye diseases in a nationally representative sample of the middle-aged and older adult population in the United States. The findings indicated that higher serum concentrations of <italic>&#x03B1;</italic>-carotene, <italic>&#x03B2;</italic>-carotene, and lutein/zeaxanthin were negatively associated with the risk of cataracts; a higher serum concentration of &#x03B2;-cryptoxanthin was negatively associated with the risk of glaucoma; higher serum concentrations of <italic>&#x03B2;</italic>-carotene and &#x03B2;-cryptoxanthin were negatively associated with the risk of diabetic retinopathy; and a higher serum concentration of lycopene was negatively associated with the risk of AMD. In addition, we discovered that serum concentrations of <italic>&#x03B1;</italic>-carotene, &#x03B2;-carotene, &#x03B2;-cryptoxanthin, lycopene, and total carotenoids were inversely associated with the risk of any ocular disease, particularly among the female participants of the present study.</p>
<p>Although the causes of age-related eye diseases are complex and multifactorial, oxidative stress is widely recognized as a common factor that contributes to the development of age-related eye diseases in middle-aged and older adults (<xref ref-type="bibr" rid="ref31">31</xref>, <xref ref-type="bibr" rid="ref32">32</xref>). The eyes are particularly vulnerable to oxidative stress due to factors such as direct exposure to ultraviolet light, a high content of mitochondria, and high metabolic activity (<xref ref-type="bibr" rid="ref2">2</xref>, <xref ref-type="bibr" rid="ref33">33</xref>). Studies have demonstrated that reactive oxygen species (ROS) can cause cataracts by damaging cell membrane fibers and crystalline proteins (<xref ref-type="bibr" rid="ref34">34</xref>). The complex non-enzymatic and enzymatic antioxidant system in the lens can scavenge ROS for preserving lens proteins, whereas the weakening of this antioxidant defense system can cause damage to lens molecules and disrupt their repair mechanisms (<xref ref-type="bibr" rid="ref35">35</xref>). Furthermore, in several studies examining the superoxide dismutase-knockdown mouse model, mice with lower levels of antioxidants were reported to exhibit higher ROS levels; these mice also displayed various AMD characteristics, including drusen, thickened Bruch&#x2019;s membrane, and choroidal neovascularization (<xref ref-type="bibr" rid="ref36 ref37 ref38">36&#x2013;38</xref>). Oxidative stress has been speculated to be involved in diabetic retinopathy. For example, studies have demonstrated that oxidative stress can alter the blood&#x2013;retinal barrier and increase vascular permeability, which are the most prominent characteristics of diabetic retinopathy (<xref ref-type="bibr" rid="ref39">39</xref>). Therefore, antioxidants may alleviate diabetic retinopathy. A study reported that the long-term administration of antioxidants inhibited the development of early-stage diabetic retinopathy in diabetic rats (<xref ref-type="bibr" rid="ref40">40</xref>).</p>
<p>A growing body of evidence suggests that carotenoids have antioxidant effects and that higher circulating concentrations of carotenoids are associated with lower risks of various oxidative stress&#x2013;related chronic diseases, such as diabetes, hypertension, and non-alcoholic fatty liver disease (<xref ref-type="bibr" rid="ref11">11</xref>, <xref ref-type="bibr" rid="ref26">26</xref>, <xref ref-type="bibr" rid="ref41">41</xref>, <xref ref-type="bibr" rid="ref42">42</xref>). Because carotenoids may be involved in cellular signaling pathways related to inflammation and oxidative stress, they may inhibit oxidative stress and inflammation (<xref ref-type="bibr" rid="ref43">43</xref>). However, to date, no systematic evaluation has examined the associations between the serum concentrations of various carotenoids and the development of age-related eye diseases, and most studies have mainly focused on single eye diseases. A meta-analysis of observational studies indicated that the serum concentration of <italic>&#x03B2;</italic>-carotene was associated with a reduced risk of cataracts (<xref ref-type="bibr" rid="ref44">44</xref>). Similarly, inverse associations were observed between the serum concentrations of <italic>&#x03B1;</italic>-carotene, lutein, and zeaxanthin and the risk of cataracts (<xref ref-type="bibr" rid="ref45">45</xref>), corresponding to our findings. To the best of our knowledge, no study has evaluated the associations between serum concentrations of carotenoids and the risk of glaucoma. Only one study reported that the dietary intake of <italic>&#x03B1;</italic>-carotene, <italic>&#x03B2;</italic>-carotene, or lutein/zeaxanthin was associated with a decreased risk of glaucoma among older African-American women. The present study also identified negative associations between the serum concentration of <italic>&#x03B1;</italic>-carotene and the risk of glaucoma among female participants (<xref ref-type="bibr" rid="ref46">46</xref>). Regarding the associations between the serum concentrations of carotenoids and the risk of diabetic retinopathy, a study reported that the plasma levels of carotenoids, including &#x03B1;-carotene, <italic>&#x03B2;</italic>-carotene, &#x03B2;-cryptoxanthin, lycopene, and lutein/zeaxanthin, were lower in individuals with diabetic retinopathy than in those without diabetic retinopathy (<xref ref-type="bibr" rid="ref47">47</xref>). Similar to our findings, the results of a cross-sectional study conducted in a Chinese population indicated that a higher serum concentration of <italic>&#x03B2;</italic>-carotene is associated with a lower risk of diabetic retinopathy, suggesting that &#x03B2;-carotene plays a protective role against diabetic retinopathy (<xref ref-type="bibr" rid="ref23">23</xref>). Furthermore, in a matched case&#x2013;control study of 164 patients with AMD, higher concentrations of carotenoids, including &#x03B2;-carotene, <italic>&#x03B2;</italic>-cryptoxanthin, lycopene, and lutein/zeaxanthin, were revealed to be inversely associated with the risk of AMD (<xref ref-type="bibr" rid="ref48">48</xref>). Our study also revealed an inverse association between the serum concentration of lycopene and the risk of AMD.</p>
<p>The results of the present study suggested that serum concentrations of <italic>&#x03B1;</italic>-carotene, <italic>&#x03B2;</italic>-carotene, &#x03B2;-cryptoxanthin, lycopene, lutein/zeaxanthin, and total carotenoids were associated with a decreased risk of any ocular disease among the female participants. By contrast, no association was identified between the serum concentrations of carotenoids and the risk of any ocular disease among the male participants. While this finding is intriguing, the underlying mechanisms remain uncertain and should be interpreted with caution. A possible explanation for this phenomenon is that relative to men, women are typically more sensitive to oxidative stress and tend to exhibit higher levels of oxidative stress (<xref ref-type="bibr" rid="ref49 ref50 ref51">49&#x2013;51</xref>). In particular, for postmenopausal women, the lack of estrogen often leads to increased oxidative stress (<xref ref-type="bibr" rid="ref52">52</xref>). In addition, women may have a higher risk of age-related eye diseases than men because of various socioeconomic factors and the effects of estrogen withdrawal during menopause (<xref ref-type="bibr" rid="ref4">4</xref>). In addition, the stronger inverse associations observed in women may reflect estrogen&#x2019;s modulation of carotenoid metabolism and absorption. For instance, scavenger receptor class B member 1 (SR-B1) is a multiligand receptor that facilitates the uptake of cholesteryl esters from high-density lipoproteins (HDLs) and the transport of carotenoids. Its expression is transcriptionally upregulated by estrogen through the direct binding of estrogen receptors to estrogen response elements (EREs) in its promoter (<xref ref-type="bibr" rid="ref53">53</xref>). This is supported by our supplementary analysis showing lower carotenoid levels in female participants compared to male participants (<xref ref-type="bibr" rid="ref54">54</xref>). However, it is important to note that these explanations remain hypothetical. Residual confounding by unmeasured socioeconomic or lifestyle factors. Therefore, our results should be seen as generating a hypothesis that warrants further investigation in studies designed specifically to explore causal mechanisms behind sex differences in carotenoid metabolism and ocular protection.</p>
<p>The present study has several strengths. First, we comprehensively assessed the associations between the serum concentrations of various carotenoids and the risk of various age-related eye diseases, including cataract, glaucoma, diabetic retinopathy, and AMD. Notably, our study is the first to explore the dose&#x2013;response relationship between the serum concentrations of various carotenoids and the risk of any ocular disease. Second, because we used data from the National Health and Nutrition Examination Survey, which is a nationally representative database, our findings can be generalized to the community-dwelling population in the United States. Third, our analyses were adjusted for an extensive set of confounders, including socioeconomic and health factors. Finally, serum carotenoid levels provide a more robust and biologically relevant measure than dietary intake estimates for studying age-related eye diseases. Unlike questionnaire-based dietary data, serum concentrations objectively reflect bioavailable carotenoid exposure, integrating absorption efficiency, metabolic variation, and contributions from both diet and supplements. Crucially, they exhibit stronger physiological plausibility for antioxidant protection in ocular tissues and, in our analyses, remained independently associated with disease risk even after adjustment for dietary intake, highlighting their value as a superior biomarker in nutritional ophthalmology research.</p>
<p>Nonetheless, the present study still has several limitations. First, because of the cross-sectional design of our study, we could not explore the causal relationship between the serum concentrations of the studied carotenoids and the development of age-related eye diseases. Second, the cohort consisted predominantly of non-Hispanic White participants, with underrepresented groups comprising a smaller proportion, which limits the generalizability of our findings. Third, our study is limited by the classification of diabetic retinopathy within the NHANES database, which did not separately identify proliferative diabetic retinopathy (PDR). Consequently, our analysis was restricted to non-proliferative stages, potentially diluting the observed effect sizes and preventing an assessment of whether higher carotenoid levels are associated with a reduced risk of progressing to sight-threatening PDR. This may result in a conservative underestimation of the true protective association. Fourth, cataract and glaucoma were defined based on self-reported data obtained during a personal interview. This method does not allow differentiation between primary open-angle glaucoma (POAG) and ocular hypertension (OHT). Since OHT is not associated with the optic nerve damage characteristic of POAG, this misclassification likely biases the observed associations toward null, thereby potentially underestimating the relationship between carotenoid levels and neurodegenerative glaucomatous pathology. Future prospective studies should incorporate detailed clinical assessments, such as optic nerve head imaging, visual field testing, to improve diagnostic accuracy and better distinguish between glaucoma subtypes. Fifth, due to constraints in the NHANES dataset, we did not exclude participants with non-age-related ocular conditions (e.g., uveitis and traumatic cataract) or a history of cataract surgery, which may introduce some potential for confounding. Furthermore, the findings of the present study could have been influenced by residual confounders, such as dietary supplementation (AREDS formulations, multivitamins) and medication use (statins, corticosteroids). Finally, the sample size of the present study was small because limited data were available, and the associations between the serum concentrations of several carotenoids and the development of age-related eye diseases approached statistical significance. Although the FDR correction was applied to mitigate the risk of false positives resulting from multiple comparisons, some significant findings may still be attributable to type I error. Therefore, our overall findings must be further verified through prospective studies with larger sample sizes.</p>
</sec>
<sec sec-type="conclusions" id="sec17">
<label>5</label>
<title>Conclusion</title>
<p>Our study demonstrated that higher serum concentrations of carotenoids, particularly <italic>&#x03B1;</italic>-carotene, <italic>&#x03B2;</italic>-carotene, &#x03B2;-cryptoxanthin, and lycopene, were associated with a lower risk of age-related eye diseases. The present findings need to be verified in prospective studies with a larger sample size.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec18">
<title>Data availability statement</title>
<p>Publicly available datasets were analyzed in this study. This data can be found at: <ext-link xlink:href="https://www.cdc.gov/nchs/nhanes/" ext-link-type="uri">https://www.cdc.gov/nchs/nhanes/</ext-link>.</p>
</sec>
<sec sec-type="ethics-statement" id="sec19">
<title>Ethics statement</title>
<p>The studies involving humans were approved by Research Ethics Review Board of the US Centers for Disease Control and the National Center for Health Statistics. 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="sec20">
<title>Author contributions</title>
<p>SC: Conceptualization, Data curation, Methodology, Software, Writing &#x2013; original draft. YM: Methodology, Project administration, Supervision, Validation, Writing &#x2013; original draft. JC: Methodology, Software, Supervision, Validation, Writing &#x2013; review &#x0026; editing.</p>
</sec>

<ack><title>Acknowledgments</title>
<p>The authors thank the investigators, the staff, and the participants of NHANES for their valuable contributions.</p>
</ack>
<sec sec-type="COI-statement" id="sec22">
<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="sec23">
<title>Generative AI statement</title>
<p>The authors declare that no Gen AI was used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="sec24">
<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="sec25">
<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/fmed.2025.1596799/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fmed.2025.1596799/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Table_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/>
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</ref-list><fn-group><fn id="fn0001" fn-type="custom" custom-type="edited-by"><p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1984798/overview">Livio Vitiello</ext-link>, Azienda Sanitaria Locale Salerno, Italy</p></fn>
<fn id="fn0002" fn-type="custom" custom-type="reviewed-by"><p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/418067/overview">Dario Rusciano</ext-link>, Consultant, Catania, Italy; <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2289032/overview">Mianli Xiao</ext-link>, University of South Florida, United States</p></fn></fn-group></back>
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