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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Nutr.</journal-id>
<journal-title>Frontiers in Nutrition</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Nutr.</abbrev-journal-title>
<issn pub-type="epub">2296-861X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fnut.2023.1215688</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Nutrition</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Association of dietary inflammatory index with sarcopenia in asthmatic patients: a cross-sectional study</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Lin</surname> <given-names>Shuqiong</given-names></name><xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="fn0004" ref-type="author-notes"><sup>&#x2020;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2292155/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes"><name><surname>Su</surname> <given-names>Xia</given-names></name><xref rid="aff2" ref-type="aff"><sup>2</sup></xref>
<xref rid="c001" ref-type="corresp"><sup>&#x002A;</sup></xref>
<xref rid="fn0004" ref-type="author-notes"><sup>&#x2020;</sup></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Chen</surname> <given-names>Liqun</given-names></name><xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="fn0004" ref-type="author-notes"><sup>&#x2020;</sup></xref>
</contrib>
<contrib contrib-type="author" corresp="yes"><name><surname>Cai</surname> <given-names>Zhiming</given-names></name><xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="c001" ref-type="corresp"><sup>&#x002A;</sup></xref>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Zhangzhou Affiliated Hospital of Fujian Medical University</institution>, <addr-line>Zhangzhou</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Longyan First Affiliated Hospital of Fujian Medical University</institution>, <addr-line>Longyan</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0005">
<p>Edited by: Tao Tong, China Agricultural University, China</p>
</fn>
<fn fn-type="edited-by" id="fn0006">
<p>Reviewed by: Asl&#x0131; U&#x00E7;ar, Ankara University, T&#x00FC;rkiye; Wei Wei Cui, Jilin University, China</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Xia Su, <email>271400181@qq.com</email>; Zhiming Cai, <email>zzsyycaizhiming@163.com</email></corresp>
<fn fn-type="equal" id="fn0004">
<p><sup>&#x2020;</sup>These authors have contributed equally to this work</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>31</day>
<month>08</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>10</volume>
<elocation-id>1215688</elocation-id>
<history>
<date date-type="received">
<day>25</day>
<month>05</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>16</day>
<month>08</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2023 Lin, Su, Chen and Cai.</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Lin, Su, Chen and Cai</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec id="sec1">
<title>Background</title>
<p>Sarcopenia is a complication of asthma, and asthmatics with sarcopenia are at an increased risk of poor prognosis. Anti-inflammatory intervention promising as an effective measure to prevent sarcopenia among patients with asthma. Diet is an important way to regulate inflammation throughout the body. The dietary inflammatory index (DII) is an index that assesses an individual&#x2019;s overall dietary inflammatory potential. The relationship between DII and sarcopenia among patients with asthma is not clear.</p>
</sec>
<sec id="sec2">
<title>Objective</title>
<p>To examine the correlation between DII and the sarcopenia among individuals with asthma.</p>
</sec>
<sec id="sec3">
<title>Methods</title>
<p>The National Health and Nutrition Examination Survey (NHANES) was the data source utilized in this study, spanning two time periods from 1999 to 2006 and 2011 to 2018. The study encompassed 3,389 participants in total. DII was calculated using the results of the participants&#x2019; 24-h dietary recall interviews. Patients were categorized into three groups based on the DII tertile: T1 group (<italic>n</italic>&#x2009;=&#x2009;1,130), T2 group (<italic>n</italic>&#x2009;=&#x2009;1,129), and T3 group (<italic>n</italic>&#x2009;=&#x2009;1,130). Logistic regression analysis, taking into account the NHANES recommended weights, was performed to assess the relationship between DII and sarcopenia.</p>
</sec>
<sec id="sec4">
<title>Results</title>
<p>After full adjustment, there was a significant positive correlation between DII levels and the risk of sarcopenia in asthmatic patients (OR: 1.27, 95% CI: 1.13&#x2013;1.42, <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001). Compared with T1 group, T3 group had higher risk of sarcopenia (T2: OR: 1.39, 95%CI: 0.88&#x2013;2.18, <italic>p</italic>&#x2009;=&#x2009;0.157; T3: OR: 2.37, 95%CI: 1.47&#x2013;3.83, <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001).</p>
</sec>
<sec id="sec5">
<title>Conclusion</title>
<p>There was a significant positive correlation between DII and the risk of sarcopenia.</p>
</sec>
</abstract>
<kwd-group>
<kwd>asthma</kwd>
<kwd>sarcopenia</kwd>
<kwd>dietary inflammatory index</kwd>
<kwd>diet</kwd>
<kwd>NHANES</kwd>
</kwd-group>
<counts>
<fig-count count="4"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="49"/>
<page-count count="10"/>
<word-count count="5804"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Clinical Nutrition</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec6">
<title>Introduction</title>
<p>Bronchial asthma, a chronic disease affecting 330 million people worldwide, is characterized by airway inflammation and hyperresponsiveness (<xref ref-type="bibr" rid="ref1">1</xref>, <xref ref-type="bibr" rid="ref2">2</xref>), with asthma patients having abnormally elevated levels of multiple inflammatory factors such as interleukin-1 (IL-1), IL-6, IL-17, and tumor necrosis factor-&#x03B1; (TNF-&#x03B1;) (<xref ref-type="bibr" rid="ref3">3</xref>). These inflammatory factors can cause skeletal muscle loss through a variety of pathways [such as nuclear factor &#x03BA;b (NF-&#x03BA;B)], leading to sarcopenia (<xref ref-type="bibr" rid="ref4">4</xref>). Sarcopenia is an emerging global health problem characterized by the gradual decline of skeletal muscle mass and can lead to adverse complications (<xref ref-type="bibr" rid="ref5">5</xref>). About 3% of the world&#x2019;s population suffers from sarcopenia (<xref ref-type="bibr" rid="ref6">6</xref>), and individuals with asthma have a higher prevalence of this condition. According to research, the prevalence of sarcopenia in individuals with asthma can be as high as 17.6%, and approximately 5.5% of asthmatic are affected by severe sarcopenia (<xref ref-type="bibr" rid="ref7">7</xref>). Furthermore, individuals with both asthma and sarcopenia were also at higher risk of osteoporosis, decreased lung function, and depression (<xref ref-type="bibr" rid="ref7">7</xref>), and asthma patients with sarcopenia experience more severe shortness of breath and airway obstruction (<xref ref-type="bibr" rid="ref8">8</xref>). Therefore, it is necessary to prevent sarcopenia among patients with asthma.</p>
<p>Inflammation is one of the causes of sarcopenia in asthmatic patients, which make anti-inflammatory intervention promising as an effective measure to prevent sarcopenia among individuals with asthma. Regulating inflammation can be achieved through dietary. Many components of the diet have been linked to inflammation. For instance, consuming higher amounts of cholesterol and carbohydrates has been found to contribute to increased levels of inflammation markers in the body (<xref ref-type="bibr" rid="ref9 ref10 ref11">9&#x2013;11</xref>). Increasing intake of dietary fiber, folic acid, and garlic has a positive effect on reducing levels of markers of inflammation (<xref ref-type="bibr" rid="ref12 ref13 ref14">12&#x2013;14</xref>). Nonetheless, due to the diversity of daily diets and the complex nature of individual food components, it remains a challenge to gage a person&#x2019;s comprehensive dietary inflammation level. Therefore, previous studies developed a dietary inflammation index (DII) that takes into account the anti-inflammatory and pro-inflammatory properties of different food components. This enables a more comprehensive evaluation of the overall extent of dietary inflammation in individuals (<xref ref-type="bibr" rid="ref15">15</xref>). Previous study has shown that asthmatic patients with elevated DII levels had a higher risk of experiencing all-cause mortality (<xref ref-type="bibr" rid="ref16">16</xref>). However, to our knowledge, few studies have investigated whether there is an association between DII and sarcopenia in asthmatic patients.</p>
<p>The objective of this investigation was to examine the correlation between DII and the sarcopenia among individuals with asthma, and to provide some valuable insights for the prevention of sarcopenia in patients with asthma.</p>
</sec>
<sec sec-type="methods" id="sec7">
<title>Methods</title>
<sec id="sec8">
<title>Study population</title>
<p>This study utilized data from the National Health and Nutrition Examination Survey (NHANES), which is sponsored by the National Center for Health Statistics (NCHS). NHANES is a sample survey conducted annually across the United States that surveys 5,000 Americans about their physical health. Two years is a cycle, and about 10,000 people are surveyed in each cycle. Through a sampling weighted analysis, the study cohort represents the entire population of the United States.</p>
<p>Due to the lack of records on skeletal muscle mass measurements during 2007&#x2013;2010, the scope of the study was confined only to those who took part in the survey between 1999&#x2013;2006 and 2011&#x2013;2018. Among the NHANES participants from 1999&#x2013;2006 to 2011&#x2013;2018, a total of 80,630 people participated in the survey over the 8&#x2009;cycles, and there were 6,266 asthma patients aged &#x2265;18. In addition, we excluded 2,743 individuals who did not possess sufficient skeletal muscle mass or body mass index (BMI) information, 133 individuals who did not have dietary data available for DII calculation, and one participant who was missing dietary weight data. Finally, a total of 3,389 individuals were included in the study (<xref rid="fig1" ref-type="fig">Figure 1</xref>).</p>
<fig position="float" id="fig1"><label>Figure 1</label>
<caption>
<p>Flowchart of the study design.</p>
</caption>
<graphic xlink:href="fnut-10-1215688-g001.tif"/>
</fig>
</sec>
<sec id="sec9">
<title>Definition of asthma</title>
<p>According to the NHANES questionnaire, &#x201C;Have you been told by a doctor that you have asthma?&#x201D; patients who answered yes were considered asthmatic.</p>
</sec>
<sec id="sec10">
<title>Primary outcome</title>
<p>The primary outcome is sarcopenia. According to the recommendations of Foundation for National Institutes of Health Osteoarthritis Biomarkers study (FNIH), men with a sarcopenia index of less than 0.789 and women with a sarcopenia index of less than 0.512 are considered to have sarcopenia, the sarcopenia index&#x2009;=&#x2009;total appendicular skeletal muscle mass (in kg)/BMI (kg/m<sup>2</sup>) (<xref ref-type="bibr" rid="ref17">17</xref>). NHANES official staff measured limb lean body mass with dual-energy X-ray absorptiometry (DXA), and calculated appendical skeletal muscle mass with the sum of limb lean body mass. In the NHANES files &#x201C;dxdllle,&#x201D; &#x201C;dxdllle,&#x201D; &#x201C;dxdrale,&#x201D; and &#x201C;dxdrlle,&#x201D; the specific values of limb lean body mass are recorded.<xref rid="fn0001" ref-type="fn"><sup>1</sup></xref></p>
</sec>
<sec id="sec11">
<title>Calculation of the DII</title>
<p>The collection of dietary information in NHANES was obtained by conducting 24-h dietary recall interviews at mobile inspection centers. In our study, we used 28 food parameters to calculate the DII. The foods included carbohydrates, proteins, total fats, alcohol, fibers, cholesterol, saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs), omega-3 fatty acids, omega-6 fatty acids, vitamin A, vitamin B1, vitamin B2, vitamin B6, vitamin B12, vitamin C, vitamin D, vitamin E, folic acid, niacin, magnesium, zinc, iron, selenium, beta-carotene, caffeine, and energy (<xref ref-type="bibr" rid="ref15">15</xref>). Since only these 28 food items in NHANES can be used to calculate DII, the total DII for only 28 foods was calculated in this study. But it has been established in previous studies that the predictive efficacy of DII remains unaffected even when calculated using only these 28 food items (<xref ref-type="bibr" rid="ref18">18</xref>). The cut points and the scoring system were shown in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 1</xref>.</p>
</sec>
<sec id="sec12">
<title>Confounding variable</title>
<p>Participants in the study self-reported their age, gender, race, smoking status, drinking status, height, and weight. BMI was calculated using their height and weight measurements. Triglycerides (TG) and total cholesterol (TC) were measured using a Hitachi Model 704 multichannel analyzer by the Coulston Foundation (Alamogordo, NM, United States) and a collaborating laboratory (Ottumwa, IA, United States). C-reactive protein (CRP) levels were quantified by the University of Washington (Seattle, WA, United States) using the latex-enhanced turbidity method after NHANES staff collected blood samples. Detailed procedures can be found in the NHANES official website.<xref rid="fn0002" ref-type="fn"><sup>2</sup></xref></p>
<p>Forced expiratory volume in the first second (FEV1)/forced vital capacity (FVC) measurements were obtained using a spirometer, which is a device that measures lung function. NHANES Respiratory Health Spirometer Procedure Manual<xref rid="fn0003" ref-type="fn"><sup>3</sup></xref> provides detailed procedures for obtaining spirometer measurements.</p>
<p>The patient&#x2019;s current medication use was determined based on their self-reported prescriptions. Anti-asthmatic agents, such as mast cell stabilizers, selective phosphodiesterase-4 inhibitors, leukotriene regulators, and inhaled corticosteroids, were considered. The identification of hypertension, diabetes mellitus (DM), chronic kidney disease (CKD), and cardiovascular disease (CVD) relied on positive answers to the inquiry &#x201C;Has a medical practitioner or any other healthcare professional ever informed you about your condition of hypertension, DM, CKD, and CVD?&#x201D; Patients with FEV1/FVC&#x2009;&#x003C;&#x2009;0.7 after inhaling beta 1 adrenergic bronchodilator medication were considered to have chronic obstructive pulmonary disease (COPD).</p>
</sec>
<sec id="sec13">
<title>Method of grouping</title>
<p>Based on the DII tertile, the patients were categorized into three groups: T1 group (DII&#x2009;&#x003C;&#x2009;0.9), T2 group (0.9&#x2009;&#x2264;&#x2009;DII&#x2009;&#x003C;&#x2009;2.7), and T3 group (DII&#x2009;&#x2265;&#x2009;2.7).</p>
</sec>
<sec id="sec14">
<title>Statistical analyses</title>
<p>According to the weighted recommended by the NHANES, participants were assigned corresponding sampling weights, and all statistical analyses used were calculated by sampling weights. The mean (weighted) and standard deviation (weighted) were used to represent continuous variables, while counts and percentages (weighted) were used to represent categorical variables. We employed ANOVA to assess differences in continuous variables across various groups, while &#x03C7;<sup>2</sup> test was leveraged to evaluate disparities in categorical variables.</p>
<p>In order to assess the correlation between the DII and sarcopenia among patients with asthma, logistic regression analysis was employed. NHANES weights were utilized to obtain estimates and probabilities. Model 1 represented the unadjusted analysis, while Model 2 accounted for age, gender, and race as adjustments. Model 3 was comprehensively adjusted to include other potential confounders such as age, gender, race/ethnicity, smoking habits, drinking habits, BMI, TG, TC, hypertension, DM, CKD, COPD, and anti-asthmatic agents. In order to investigate possible non-linear connections between DII and the sarcopenia among patients with asthma, a regression cubic spline (RCS) was utilized. Furthermore, a stratified analysis was conducted based on age, gender, BMI, smoking, COPD, hypertension, DM, and anti-asthmatic agents.</p>
<p>Data analyses were carried out using the Survey package in R Studio (version 4.2.2). Statistical significance was determined based on a <italic>p</italic> value of less than 0.05.</p>
</sec>
</sec>
<sec sec-type="results" id="sec15">
<title>Results</title>
<sec id="sec16">
<title>Participant characteristics</title>
<p>The study encompassed 3,389 participants in total. Participants were 39.0 (0.4) years old on average and were more likely to be female [<italic>n</italic>&#x2009;=&#x2009;1,870(55.1%)]. Based on their DII tertile, the participants were categorized into three distinct groups: T1 (<italic>n</italic>&#x2009;=&#x2009;1,130), T2 (<italic>n</italic>&#x2009;=&#x2009;1,129), and T3 (<italic>n</italic>&#x2009;=&#x2009;1,130). There were statistical differences in the proportion of female [T1: 484 (41.5%) vs. T2: 631 (56.7%) vs. T3: 755 (70.4%); <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001], drinkers [T1: 823 (83.5%) vs. T2: 714 (76.3%) vs. T3: 672 (72.0%); <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001], DM [T1: 101 (5.8%) vs. T2: 134 (9.3%) vs. T3: 139 (11.1%); <italic>p</italic>&#x2009;=&#x2009;0.001], and COPD [T1: 70 (7.4%) vs. T2: 88 (7.7%) vs. T3: 117 (11.7%); <italic>p</italic>&#x2009;=&#x2009;0.042] among the three groups. And there were statistical differences in BMI (T1: 27.7&#x2009;&#x00B1; 6.4 kg/m<sup>2</sup> vs. T2: 28.6&#x2009;&#x00B1; 6.8 kg/m<sup>2</sup> vs. T3: 29.4&#x2009;&#x00B1;&#x2009;7.4&#x2009;kg/m<sup>2</sup>; <italic>p</italic> &#x003C;&#x2009;0.001) and CRP (T1: 0.3&#x2009;&#x00B1;&#x2009;0.6&#x2009;mg/dL vs. T2: 0.4&#x2009;&#x00B1;&#x2009;0.6&#x2009;mg/dL vs. T3: 0.6&#x2009;&#x00B1;&#x2009;0.8&#x2009;mg/dL; <italic>p</italic> &#x003C;&#x2009;0.001) among the three groups. Among the three groups, there were no statistical difference in terms of age, smoking status, TG and TC levels, use of anti-asthmatic medication, presence of hypertension, and CKD (<xref rid="tab1" ref-type="table">Table 1</xref>).</p>
<table-wrap position="float" id="tab1"><label>Table 1</label>
<caption>
<p>Baseline study population characteristics (weighted).</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Variable</th>
<th align="center" valign="top">Total (<italic>n</italic>&#x2009;=&#x2009;3,389)</th>
<th align="center" valign="top">T1 group (<italic>n</italic>&#x2009;=&#x2009;1,130)</th>
<th align="center" valign="top">T2 group (<italic>n</italic>&#x2009;=&#x2009;1,129)</th>
<th align="center" valign="top">T3 group (<italic>n</italic>&#x2009;=&#x2009;1,130)</th>
<th align="center" valign="top"><italic>p</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">DII</td>
<td align="center" valign="top">1.4&#x2009;&#x00B1;&#x2009;1.9</td>
<td align="center" valign="top">&#x2212;0.6&#x2009;&#x00B1; 1.2</td>
<td align="center" valign="top">1.8&#x2009;&#x00B1;&#x2009;0.5</td>
<td align="center" valign="top">3.4&#x2009;&#x00B1;&#x2009;0.5</td>
<td align="center" valign="middle">&#x003C; 0.001<sup>+</sup></td>
</tr>
<tr>
<td align="left" valign="middle">Age, years</td>
<td align="center" valign="middle">39.0&#x2009;&#x00B1;&#x2009;14.6</td>
<td align="center" valign="middle">38.9&#x2009;&#x00B1;&#x2009;14.3</td>
<td align="center" valign="middle">39.8&#x2009;&#x00B1;&#x2009;15.1</td>
<td align="center" valign="middle">38.3&#x2009;&#x00B1;&#x2009;14.6</td>
<td align="center" valign="middle">0.248<sup>+</sup></td>
</tr>
<tr>
<td align="left" valign="middle">Female, <italic>n</italic> (%)</td>
<td align="center" valign="middle">1,870 (55.1)</td>
<td align="center" valign="middle">484 (41.5)</td>
<td align="center" valign="middle">631 (56.7)</td>
<td align="center" valign="middle">755 (70.4)</td>
<td align="center" valign="middle">&#x003C; 0.001<sup>#</sup></td>
</tr>
<tr>
<td align="left" valign="middle">Race, <italic>n</italic> (%)</td>
<td/>
<td/>
<td/>
<td/>
<td align="center" valign="middle">0.001<sup>#</sup></td>
</tr>
<tr>
<td align="left" valign="middle">Mexican American</td>
<td align="center" valign="middle">413 (6.1)</td>
<td align="center" valign="middle">134 (6.0)</td>
<td align="center" valign="middle">147 (6.4)</td>
<td align="center" valign="middle">132 (5.9)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Non-Hispanic black</td>
<td align="center" valign="middle">834 (12.6)</td>
<td align="center" valign="middle">234 (9.4)</td>
<td align="center" valign="middle">296 (15.3)</td>
<td align="center" valign="middle">304 (13.7)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Non-Hispanic white</td>
<td align="center" valign="middle">1,583 (69.2)</td>
<td align="center" valign="middle">569 (73.9)</td>
<td align="center" valign="middle">491 (64.3)</td>
<td align="center" valign="middle">523 (68.3)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Other Hispanic</td>
<td align="center" valign="middle">239 (5.8)</td>
<td align="center" valign="middle">65 (4.3)</td>
<td align="center" valign="middle">93 (7.2)</td>
<td align="center" valign="middle">81 (6.3)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Other race</td>
<td align="center" valign="middle">320 (6.3)</td>
<td align="center" valign="middle">128 (6.4)</td>
<td align="center" valign="middle">102 (6.8)</td>
<td align="center" valign="middle">90 (5.8)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Smoke status, <italic>n</italic> (%)</td>
<td align="center" valign="middle">1,452 (48.8)</td>
<td align="center" valign="middle">461 (46.2)</td>
<td align="center" valign="middle">477 (47.9)</td>
<td align="center" valign="middle">514 (53.1)</td>
<td align="center" valign="middle">0.087<sup>#</sup></td>
</tr>
<tr>
<td align="left" valign="middle">Drink status, <italic>n</italic> (%)<xref rid="tfn1" ref-type="table-fn"><sup>&#x002A;</sup></xref></td>
<td align="center" valign="middle">2,209 (77.8)</td>
<td align="center" valign="middle">823 (83.5)</td>
<td align="center" valign="middle">714 (76.3)</td>
<td align="center" valign="middle">672 (72.0)</td>
<td align="center" valign="middle">&#x003C; 0.001<sup>#</sup></td>
</tr>
<tr>
<td align="left" valign="middle">BMI, kg/m<sup>2</sup></td>
<td align="center" valign="middle">28.5&#x2009;&#x00B1; 6.9</td>
<td align="center" valign="middle">27.7&#x2009;&#x00B1; 6.4</td>
<td align="center" valign="middle">28.6&#x2009;&#x00B1; 6.8</td>
<td align="center" valign="middle">29.4&#x2009;&#x00B1;&#x2009;7.4</td>
<td align="center" valign="middle">&#x003C; 0.001<sup>+</sup></td>
</tr>
<tr>
<td align="left" valign="middle">TG, mmol/L</td>
<td align="center" valign="middle">1.7&#x2009;&#x00B1; 2.3</td>
<td align="center" valign="middle">1.7&#x2009;&#x00B1; 3.0</td>
<td align="center" valign="middle">1.7&#x2009;&#x00B1;&#x2009;1.8</td>
<td align="center" valign="middle">1.6&#x2009;&#x00B1;&#x2009;1.5</td>
<td align="center" valign="middle">0.593<sup>+</sup></td>
</tr>
<tr>
<td align="left" valign="middle">TC, mmol/L</td>
<td align="center" valign="middle">5.0&#x2009;&#x00B1; 1.3</td>
<td align="center" valign="middle">5.0&#x2009;&#x00B1; 1.2</td>
<td align="center" valign="middle">5.1&#x2009;&#x00B1;&#x2009;1.2</td>
<td align="center" valign="middle">5.0&#x2009;&#x00B1;&#x2009;1.2</td>
<td align="center" valign="middle">0.599<sup>+</sup></td>
</tr>
<tr>
<td align="left" valign="middle">CRP, mg/dL</td>
<td align="center" valign="middle">0.4&#x2009;&#x00B1;&#x2009;0.7</td>
<td align="center" valign="middle">0.3&#x2009;&#x00B1;&#x2009;0.6</td>
<td align="center" valign="middle">0.4&#x2009;&#x00B1;&#x2009;0.6</td>
<td align="center" valign="middle">0.6&#x2009;&#x00B1;&#x2009;0.8</td>
<td align="center" valign="middle">&#x003C; 0.001<sup>+</sup></td>
</tr>
<tr>
<td align="left" valign="middle">Anti-asthmatic agents, <italic>n</italic> (%)</td>
<td align="center" valign="middle">394 (12.3)</td>
<td align="center" valign="middle">127 (12.0)</td>
<td align="center" valign="middle">124 (10.6)</td>
<td align="center" valign="middle">143 (14.5)</td>
<td align="center" valign="middle">0.159<sup>#</sup></td>
</tr>
<tr>
<td align="left" valign="middle">DM, <italic>n</italic> (%)</td>
<td align="center" valign="middle">374 (8.5)</td>
<td align="center" valign="middle">101 (5.8)</td>
<td align="center" valign="middle">134 (9.3)</td>
<td align="center" valign="middle">139 (11.1)</td>
<td align="center" valign="middle">0.001<sup>#</sup></td>
</tr>
<tr>
<td align="left" valign="middle">Hypertension, <italic>n</italic> (%)</td>
<td align="center" valign="middle">1,105 (29.9)</td>
<td align="center" valign="middle">346 (27.4)</td>
<td align="center" valign="middle">387 (31.3)</td>
<td align="center" valign="middle">372 (31.6)</td>
<td align="center" valign="middle">0.187<sup>#</sup></td>
</tr>
<tr>
<td align="left" valign="middle">CKD, <italic>n</italic> (%)</td>
<td align="center" valign="middle">397 (10.0)</td>
<td align="center" valign="middle">109 (8.6)</td>
<td align="center" valign="middle">149 (10.3)</td>
<td align="center" valign="middle">139 (11.2)</td>
<td align="center" valign="middle">0.293<sup>#</sup></td>
</tr>
<tr>
<td align="left" valign="middle">COPD, <italic>n</italic> (%)</td>
<td align="center" valign="middle">275 (8.8)</td>
<td align="center" valign="middle">70 (7.4)</td>
<td align="center" valign="middle">88 (7.7)</td>
<td align="center" valign="middle">117 (11.7)</td>
<td align="center" valign="middle">0.042<sup>#</sup></td>
</tr>
<tr>
<td align="left" valign="middle">Sarcopenia, <italic>n</italic> (%)</td>
<td align="center" valign="middle">347 (10.2)</td>
<td align="center" valign="middle">85 (5.8)</td>
<td align="center" valign="middle">112 (7.6)</td>
<td align="center" valign="middle">150 (12.2)</td>
<td align="center" valign="middle">&#x003C; 0.001<sup>#</sup></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Values are, <italic>n</italic> (%) or mean &#x00B1;&#x2009;SD. <sup>+</sup>ANOVA test; <sup>#</sup><italic>&#x03C7;</italic><sup>2</sup> test. DII, dietary inflammation index; BMI, body mass index; CRP: C-reactive protein; TG, triglyceride; TC, total cholesterol; DM, diabetes; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease.</p>
<fn id="tfn1"><label>&#x002A;</label>
<p>The average number of drinks consumed per day over the past 12&#x2009;months.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec17">
<title>Relationship between DII and sarcopenia</title>
<p>As shown in <xref rid="fig2" ref-type="fig">Figure 2</xref>, individuals with higher levels of DII exhibited a greater prevalence of sarcopenia (T1: 5.8% vs. T2: 7.6% vs. T3: 12.2%). Through the implementation of univariate logistic regression analysis, it was found that a significant positive correlation between DII and the risk of sarcopenia [odds ratio (OR): 1.26, 95% CI: 1.15&#x2013;1.39, <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001; Model 1]. In contrast to the T1 group, only the T3 group had a higher risk of sarcopenia (OR: 2.26, 95%CI: 1.56&#x2013;3.29; <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001; Model 1). After adjusting for age, gender and race, the positive correlation between DII and sarcopenia remained statistically significant (OR: 1.35, 95% CI: 1.21&#x2013;1.49, <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001; Model 2). Participants in T3 group had a higher risk of sarcopenia (OR: 2.87, 95%CI: 1.93&#x2013;4.26; <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001; Model 2). Moreover, when accounting for all potential confounders, the relationship between DII and sarcopenia remained statistically significant (OR: 1.27, 95% CI: 1.13&#x2013;1.42, <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001; Model 3). Furthermore, participants in the T3 group continued to exhibit a higher risk of sarcopenia (OR: 2.37, 95%CI: 1.47&#x2013;3.83; <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001; Model 3). Additional details can be found in <xref rid="tab2" ref-type="table">Table 2</xref>.</p>
<fig position="float" id="fig2"><label>Figure 2</label>
<caption>
<p>Prevalence of sarcopenia in different groups (weighted). DII, dietary inflammation index; BMI, body mass index.</p>
</caption>
<graphic xlink:href="fnut-10-1215688-g002.tif"/>
</fig>
<table-wrap position="float" id="tab2"><label>Table 2</label>
<caption>
<p>The association between DII and sarcopenia (weighted).</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Variable</th>
<th align="center" valign="top" colspan="2">Model 1</th>
<th align="center" valign="top" colspan="2">Model 2</th>
<th align="center" valign="top" colspan="2">Model 3</th>
</tr>
<tr>
<th align="center" valign="top">OR (95%CI)</th>
<th align="center" valign="top"><italic>p</italic> value</th>
<th align="center" valign="top">OR (95%CI)</th>
<th align="center" valign="top"><italic>p</italic> value</th>
<th align="center" valign="top">OR (95%CI)</th>
<th align="center" valign="top"><italic>p</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="bottom">Continuous variables</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="bottom">DII</td>
<td align="center" valign="bottom">1.26 (1.15&#x2013;1.39)</td>
<td align="center" valign="middle">&#x003C;0.001</td>
<td align="center" valign="bottom">1.35 (1.21,1.49)</td>
<td align="center" valign="middle">&#x003C;0.001</td>
<td align="center" valign="bottom">1.27 (1.13,1.42)</td>
<td align="center" valign="middle">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Categorical variable</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">T1 group</td>
<td align="center" valign="middle">Ref</td>
<td/>
<td align="center" valign="middle">Ref</td>
<td/>
<td align="center" valign="middle">Ref</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">T2 group</td>
<td align="center" valign="middle">1.35 (0.93,1.95)</td>
<td align="center" valign="middle">0.110</td>
<td align="center" valign="middle">1.41 (0.97,2.04)</td>
<td align="center" valign="middle">0.068</td>
<td align="center" valign="middle">1.39 (0.88,2.18)</td>
<td align="center" valign="middle">0.157</td>
</tr>
<tr>
<td align="left" valign="middle">T3 group</td>
<td align="center" valign="middle">2.26 (1.56,3.29)</td>
<td align="center" valign="middle">&#x003C;0.001</td>
<td align="center" valign="middle">2.87 (1.93,4.26)</td>
<td align="center" valign="middle">&#x003C;0.001</td>
<td align="center" valign="middle">2.37 (1.47,3.83)</td>
<td align="center" valign="middle">&#x003C;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Model 1: Not adjusted. Model 2: Adjusted by age, gender, and race. Model 3: Adjusted by age, gender, race, smoke, drink, BMI, TG, TC, hypertension, DM, CKD, COPD, and anti-asthmatic agents.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec18">
<title>Regression cubic splines</title>
<p>Regression cubic spline adjusted for Model 3 showed that DII was positively correlated with the risk of sarcopenia in asthmatic patients. No nonlinear relationship was observed between DII and sarcopenia (Non-linear <italic>p</italic>&#x2009;=&#x2009;0.488; <xref rid="fig3" ref-type="fig">Figure 3</xref>).</p>
<fig position="float" id="fig3"><label>Figure 3</label>
<caption>
<p>Potential nonlinear relationship between DII and sarcopenia (weighted). Adjusted for age, sex, race/ethnicity, smoking, drinking, BMI, TG, TC, hypertension, DM, CKD, COPD, and anti-asthma medications. DII, dietary inflammation index; BMI, body mass index; TG, triglyceride; TC, total cholesterol; DM, diabetes; CKD, Chronic kidney disease; and COPD: Chronic obstructive pulmonary disease.</p>
</caption>
<graphic xlink:href="fnut-10-1215688-g003.tif"/>
</fig>
</sec>
<sec id="sec19">
<title>Subgroup analysis</title>
<p>No alteration was observed in the association between DII and sarcopenia when conducting a stratified analysis according to age (<italic>p</italic> for interaction&#x2009;=&#x2009;0.907), sex (<italic>p</italic> for interaction&#x2009;=&#x2009;0.804), BMI (<italic>p</italic> for interaction&#x2009;=&#x2009;0.707), smoking (<italic>p</italic> for interaction&#x2009;=&#x2009;0.929), COPD (<italic>p</italic> for interaction&#x2009;=&#x2009;0.403), hypertension (<italic>p</italic> for interaction&#x2009;=&#x2009;0.803), DM (<italic>p</italic> for interaction&#x2009;=&#x2009;0.657), and antiasthmatic drugs (<italic>p</italic> for interaction&#x2009;=&#x2009;0.440; <xref rid="fig4" ref-type="fig">Figure 4</xref>).</p>
<fig position="float" id="fig4"><label>Figure 4</label>
<caption>
<p>Association between DII and sarcopenia by selected subgroups (weighted). Adjusted for age, sex, race/ethnicity, smoking, drinking, BMI, TG, TC, hypertension, DM, CKD, COPD, and anti-asthma medications. When stratified, stratified variables are not adjusted. DII, dietary inflammation index; BMI, body mass index; TG, triglyceride; TC, total cholesterol; DM, diabetes; CKD, chronic kidney disease; and COPD: chronic obstructive pulmonary disease.</p>
</caption>
<graphic xlink:href="fnut-10-1215688-g004.tif"/>
</fig>
</sec>
</sec>
<sec sec-type="discussions" id="sec20">
<title>Discussion</title>
<p>A total of 3,389 asthmatic patients were enrolled in this study. Our findings indicate a noteworthy positive correlation between the DII and sarcopenia among asthmatic patients. After stratification by age, sex, BMI, smoking, COPD, hypertension, DM and antiasthmatic drugs, no substantial alteration in the correlation between DII and sarcopenia was observed.</p>
<p>According to a meta-analysis, an elevated DII level was found to be significantly linked to the occurrence and progression of chronic illnesses, including CVD, cancer, and respiratory disease (<xref ref-type="bibr" rid="ref19">19</xref>). In a study conducted on individuals with asthma, Han et al. (<xref ref-type="bibr" rid="ref20">20</xref>) demonstrated that a higher DII level was connected to an elevated risk of wheezing. Additionally, Yuan et al. (<xref ref-type="bibr" rid="ref16">16</xref>) observed that asthmatic patients with elevated DII levels had a higher risk of experiencing all-cause mortality. Nevertheless, the relationship between DII and sarcopenia in asthmatic individuals remains poorly investigated.</p>
<p>Several studies have demonstrated that increased levels of DII are a risk factor for the onset of sarcopenia in older adults (<xref ref-type="bibr" rid="ref21 ref22 ref23">21&#x2013;23</xref>). Similarly, heightened DII have also been linked to an elevated risk of sarcopenia in patients with DM, hypertension, Crohn&#x2019;s disease, and CKD (<xref ref-type="bibr" rid="ref24 ref25 ref26">24&#x2013;26</xref>). It is well-established that aging is associated with a chronic state of low-grade inflammation in older adults (<xref ref-type="bibr" rid="ref27">27</xref>). Many studies observed elevated levels of proinflammatory factors in the blood of people with hypertension and diabetes (<xref ref-type="bibr" rid="ref28">28</xref>, <xref ref-type="bibr" rid="ref29">29</xref>). Additionally, both Crohn&#x2019;s disease and CKD are characterized by persistent inflammation (<xref ref-type="bibr" rid="ref30">30</xref>, <xref ref-type="bibr" rid="ref31">31</xref>). Like these population, asthma is also a chronic inflammatory disease (<xref ref-type="bibr" rid="ref32">32</xref>), and studies have shown that people with asthma were more susceptible to the pro-inflammatory effects of dietary factors when compared to those without asthma (<xref ref-type="bibr" rid="ref20">20</xref>). Furthermore, it should be noted that numerous asthma drugs have been found to contribute to the development of sarcopenia (<xref ref-type="bibr" rid="ref33">33</xref>, <xref ref-type="bibr" rid="ref34">34</xref>). Sarcopenia in patients may exacerbate their asthma symptoms, thereby necessitating more anti-asthma medication, leading to a vicious cycle. Therefore, as with the elderly, DM, hypertension, Crohn&#x2019;s disease, and CKD patients, the prevention of sarcopenia in asthma patients is also worthy of attention. Our study fills a gap in this area by using DII to assess the risk of sarcopenia among patients with asthma. Our findings suggest that DII was significantly correlated with the risk of sarcopenia in patients with asthma. Following the adjustment for potential confounders, the relationship between the two did not change significantly. In addition, stratified results by age, sex, BMI, smoking, hypertension, diabetes, and anti-asthma medications did not change significantly, and no interaction was observed between DII and these variables.</p>
<p>The mechanism by which a pro-inflammatory diet induces sarcopenia in asthmatic patients is unclear, but previous studies have provided some theoretical evidence. The study suggests that trans fatty acids have been shown to increase airway inflammation and circulating CRP levels in asthma patients (<xref ref-type="bibr" rid="ref35">35</xref>, <xref ref-type="bibr" rid="ref36">36</xref>). In addition, inflammatory factors such as platelet-derived growth factor (PDGF), interferon-&#x03B3; (IFN-&#x03B3;), IL-1, and TNF-&#x03B1; were significantly increased in mice with high cholesterol intake (<xref ref-type="bibr" rid="ref37">37</xref>). Excessive intake of refined carbohydrates increases circulating TNF-&#x03B1; levels via the NF-&#x03BA;B pathway (<xref ref-type="bibr" rid="ref38">38</xref>). In contrast, ingestion of PUFAs produces anti-inflammatory mediators and inhibits the production of pro-inflammatory factors (<xref ref-type="bibr" rid="ref39">39</xref>). A randomized controlled trial confirmed that increasing MUFAs intake helped lower CRP and IL-6 (<xref ref-type="bibr" rid="ref40">40</xref>). TNF-&#x03B1; can induce sarcopenia through pyrodeath mediated by Gasdermins (<xref ref-type="bibr" rid="ref41">41</xref>). IL-6 can be indicated by glycoprotein 130 (gp130)/Janus kinase (JAK)/Signal Transducer and Activator of Transcription (STAT)/Suppressor of Cytokine Signaling (SOCS) pathways increase protein degradation and decrease protein synthesis to mediate skeletal muscle atrophy (<xref ref-type="bibr" rid="ref42">42</xref>). Britta Walling-Larsson et al. (<xref ref-type="bibr" rid="ref43">43</xref>) indicated that CRP can lead to downregulation of serine/threonine kinase Akt promoting muscle atrophy. PDGF can cause muscle fibrosis and hinder muscle repair by activating RHO-associated kinases (<xref ref-type="bibr" rid="ref44">44</xref>). IFN-&#x03B3; interferes with the differentiation of muscle satellite cells, leading to the accumulation of muscle satellite cells and the loss of skeletal muscle mass (<xref ref-type="bibr" rid="ref4">4</xref>). Therefore, the loss of muscle mass caused by a pro-inflammatory diet may result from a number of pathways.</p>
<p>It should be emphasized that the correlation between protein and inflammation is not solely linked to consumption but also to the origin of protein. Animal-derived proteins lead to increased levels of pro-inflammatory factors, while plant-derived proteins help reduce inflammation throughout the body (<xref ref-type="bibr" rid="ref36">36</xref>). A recent study showed that intake of animal protein increases the risk of developing frailty (a phenotypic manifestation of sarcopenia) (<xref ref-type="bibr" rid="ref45 ref46 ref47">45&#x2013;47</xref>), while increasing plant protein intake was linked with a lower possibility of developing frailty (<xref ref-type="bibr" rid="ref48">48</xref>, <xref ref-type="bibr" rid="ref49">49</xref>). Therefore, when consuming protein, choosing to consume more plant protein may help prevent sarcopenia.</p>
<p>As mentioned above, the major pro-inflammatory parameters in DII, such as carbohydrates, cholesterol, trans fatty acids and animal protein, were strongly associated with the onset and development of sarcopenia. Thus, reducing the consumption of these pro-inflammatory components may yield beneficial effects in preventing sarcopenia. Increasing the intake of anti-inflammatory food components such as PUFAs, MUFAs, and plant proteins in DII can reduce the level of inflammation throughout the body and is one of the potential interventions to prevent sarcopenia. Therefore, we recommend that people with asthma reduce their intake of pro-inflammatory food components in the DII dietary pattern and increase their intake of anti-inflammatory food components. Although a causal relationship between DII and sarcopenia in asthmatic patients need to be further confirmed in randomized clinical trials. However, prior research has established that patients with asthma experienced a decrease in wheezing attacks and all-cause mortality by maintaining low levels of DII. Therefore, despite being a cross-sectional study, we still recommend that patients with asthma adopt a healthy low-DII dietary pattern.</p>
<sec id="sec21">
<title>Limitations</title>
<p>There are certain constraints inherent in our study. Initially, due to its cross-sectional design, we can only establish a correlation between the DII and sarcopenia in asthmatic patients, rather than establish a causal relationship. Secondly, relying solely on self-reported questionnaires to diagnose asthmatics may underestimate the number of asthmatics. Third, assessing DII solely on the basis of 24-h dietary recall may not be representative of patients&#x2019; long-term dietary patterns, and further clinical randomized controlled trials are needed to further corroborate our results.</p>
</sec>
</sec>
<sec sec-type="conclusions" id="sec22">
<title>Conclusion</title>
<p>There was a significant positive correlation between DII and the risk of sarcopenia. However, additional randomized controlled trials are necessary to establish a definitive causal connection between the DII and the onset of sarcopenia.</p>
</sec>
<sec sec-type="data-availability" id="sec23">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="sec24">
<title>Ethics statement</title>
<p>The studies involving humans were approved by National Center for Health Statistics. The studies were conducted in accordance with the local legislation and institutional requirements. The human samples used in this study were acquired from this study utilized data from the National Health and Nutrition Examination Survey (NHANES), which is sponsored by the National Center for Health Statistics (NCHS). Written informed consent for participation was not required from the participants or the participants&#x2019; legal guardians/next of kin in accordance with the national legislation and institutional requirements.</p>
</sec>
<sec id="sec25">
<title>Author contributions</title>
<p>ZC designed the research and is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. SL conducted the analysis and wrote the first draft of the paper. SL, XS, LC, and ZC revised the manuscript. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec sec-type="COI-statement" id="sec27">
<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 id="sec100" sec-type="disclaimer">
<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>
</body>
<back>
<sec sec-type="supplementary-material" id="sec28">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fnut.2023.1215688/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fnut.2023.1215688/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"/>
</sec>
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</ref-list>
<sec id="sec26">
<title>Glossary</title>
<table-wrap position="anchor" id="tab3">
<table frame="hsides" rules="groups">
<tbody>
<tr>
<td align="left" valign="top">IL</td>
<td align="left" valign="top">Interleukin</td>
</tr>
<tr>
<td align="left" valign="top">TNF-&#x03B1;</td>
<td align="left" valign="top">Tumor necrosis factor-&#x03B1;</td>
</tr>
<tr>
<td align="left" valign="top">NF-&#x03BA;B</td>
<td align="left" valign="top">Nuclear factor &#x03BA;b</td>
</tr>
<tr>
<td align="left" valign="top">DII</td>
<td align="left" valign="top">Dietary inflammation index</td>
</tr>
<tr>
<td align="left" valign="top">NHANES</td>
<td align="left" valign="top">National Health and Nutrition Examination Survey</td>
</tr>
<tr>
<td align="left" valign="top">NCHS</td>
<td align="left" valign="top">National Center for Health Statistics</td>
</tr>
<tr>
<td align="left" valign="top">FNIH</td>
<td align="left" valign="top">Foundation for National Institutes of Health Osteoarthritis Biomarkers study</td>
</tr>
<tr>
<td align="left" valign="top">DXA</td>
<td align="left" valign="top">Dual-energy X-ray absorptiometry</td>
</tr>
<tr>
<td align="left" valign="top">BMI</td>
<td align="left" valign="top">Body mass index</td>
</tr>
<tr>
<td align="left" valign="top">SFAs</td>
<td align="left" valign="top">Saturated fatty acids</td>
</tr>
<tr>
<td align="left" valign="top">MUFAs</td>
<td align="left" valign="top">Monounsaturated fatty acids</td>
</tr>
<tr>
<td align="left" valign="top">PUFAs</td>
<td align="left" valign="top">Polyunsaturated fatty acids</td>
</tr>
<tr>
<td align="left" valign="top">TG</td>
<td align="left" valign="top">Triglycerides</td>
</tr>
<tr>
<td align="left" valign="top">TC</td>
<td align="left" valign="top">Total cholesterol</td>
</tr>
<tr>
<td align="left" valign="top">DM</td>
<td align="left" valign="top">Diabetes mellitus</td>
</tr>
<tr>
<td align="left" valign="top">CKD</td>
<td align="left" valign="top">Chronic kidney disease</td>
</tr>
<tr>
<td align="left" valign="top">CVD</td>
<td align="left" valign="top">Cardiovascular disease</td>
</tr>
<tr>
<td align="left" valign="top">FEV1</td>
<td align="left" valign="top">Forced expiratory volume in the first second</td>
</tr>
<tr>
<td align="left" valign="top">FVC</td>
<td align="left" valign="top">Forced vital capacity</td>
</tr>
<tr>
<td align="left" valign="top">COPD</td>
<td align="left" valign="top">Chronic obstructive pulmonary disease</td>
</tr>
<tr>
<td align="left" valign="top">ANOVA</td>
<td align="left" valign="top">Analysis of variance</td>
</tr>
<tr>
<td align="left" valign="top">RCS</td>
<td align="left" valign="top">Regression cubic spline</td>
</tr>
<tr>
<td align="left" valign="top">CRP</td>
<td align="left" valign="top">C-reactive protein</td>
</tr>
<tr>
<td align="left" valign="top">PDGF</td>
<td align="left" valign="top">Platelet-derived growth factor</td>
</tr>
<tr>
<td align="left" valign="top">IFN-&#x03B3;</td>
<td align="left" valign="top">Interferon-&#x03B3;</td>
</tr>
<tr>
<td align="left" valign="top">gp130</td>
<td align="left" valign="top">Glycoprotein 130</td>
</tr>
<tr>
<td align="left" valign="top">JAK</td>
<td align="left" valign="top">Janus kinase</td>
</tr>
<tr>
<td align="left" valign="top">STAT</td>
<td align="left" valign="top">Signal transducer and activator of transcription</td>
</tr>
<tr>
<td align="left" valign="top">SOCS</td>
<td align="left" valign="top">Suppressor of cytokine signaling</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<fn-group>
<fn id="fn0001">
<p><sup>1</sup><ext-link xlink:href="https://wwwn.cdc.gov/nchs/data/nhanes/dxa/dxx_b.pdf" ext-link-type="uri">https://wwwn.cdc.gov/nchs/data/nhanes/dxa/dxx_b.pdf</ext-link></p>
</fn>
<fn id="fn0002">
<p><sup>2</sup><ext-link xlink:href="https://wwwn.cdc.gov/nchs/data/nhanes/2009-2010/manuals/lab.pdf" ext-link-type="uri">https://wwwn.cdc.gov/nchs/data/nhanes/2009-2010/manuals/lab.pdf</ext-link></p>
</fn>
<fn id="fn0003">
<p><sup>3</sup><ext-link xlink:href="https://wwwn.cdc.gov/nchs/data/nhanes/2007-2008/manuals/spirometry.pdf" ext-link-type="uri">https://wwwn.cdc.gov/nchs/data/nhanes/2007-2008/manuals/spirometry.pdf</ext-link></p>
</fn>
</fn-group>
</back>
</article>