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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Nutr.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Nutrition</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Nutr.</abbrev-journal-title>
</journal-title-group>
<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.2026.1769535</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>Adherence to plant-based diet and risk of heart failure among middle-aged and older population</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Chang</surname>
<given-names>Xiao-Xin</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhu</surname>
<given-names>Yong-Jian</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1139771"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x0026; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &#x0026; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Che</surname>
<given-names>Wen-Liang</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Li</surname>
<given-names>Yi-Ming</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3317242"/>
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</contrib-group>
<aff id="aff1"><label>1</label><institution>Department of Cardiology, Shanghai Tenth People&#x2019;s Hospital, Tongji University School of Medicine</institution>, <city>Shanghai</city>, <country country="cn">China</country></aff>
<aff id="aff2"><label>2</label><institution>Department of Cardiology, The First Affiliated Hospital of Zhengzhou University</institution>, <city>Zhengzhou</city>, <country country="cn">China</country></aff>
<aff id="aff3"><label>3</label><institution>Department of Cardiac Function, The Third Affiliated Hospital of Zhengzhou University</institution>, <city>Zhengzhou</city>, <country country="cn">China</country></aff>
<author-notes>
<corresp id="c001"><label>&#x002A;</label>Correspondence: Wen-Liang Che, <email xlink:href="mailto:chewenliang@tongji.edu.cn">chewenliang@tongji.edu.cn</email>; Yi-Ming Li, <email xlink:href="mailto:piratelim@163.com">piratelim@163.com</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-02-25">
<day>25</day>
<month>02</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>13</volume>
<elocation-id>1769535</elocation-id>
<history>
<date date-type="received">
<day>23</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>06</day>
<month>02</month>
<year>2026</year>
</date>
<date date-type="accepted">
<day>10</day>
<month>02</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2026 Chang, Zhu, Che and Li.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Chang, Zhu, Che and Li</copyright-holder>
<license>
<ali:license_ref start_date="2026-02-25">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>
<title>Background</title>
<p>Plant-based diets have been demonstrated to be associated with lower risk of several chronic diseases. However, a comprehensive assessment of plant-based diet quality and its association with heart failure (HF) is limited. This study aimed to investigate whether healthful and unhealthful plant-based dietary patterns are associated with overall HF risk among middle-aged and older adults in the United Kingdom.</p>
</sec>
<sec>
<title>Methods</title>
<p>We included a total of 190,092 UK Biobank participants without HF at baseline. Three plant-based diet indices were calculated using 24-h dietary recalls based on 17 food groups: the overall plant-based diet index (PDI), healthful plant-based diet index (hPDI), and unhealthful plant-based diet index (uPDI). Multivariable Cox regression models were applied to assess the association between these indices and incident HF.</p>
</sec>
<sec>
<title>Results</title>
<p>Over a median follow-up of 13.04&#x202F;years, 4,351 cases of new-onset HF were recorded. Compared to the lowest tertile, the multivariable-adjusted hazard ratios (HRs) with 95% confidence interval (CI) for HF in the highest tertile were 0.94 (0.88&#x2013;1.02) for overall PDI, 0.84 (0.78&#x2013;0.91) for hPDI, and 1.11 (1.03&#x2013;1.19) for uPDI.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>A higher intake of healthful plant-based diets was associated with a lower risk of HF, while follow unhealthful plant-based diet was linked to a higher overall HF risk. Adhering to a high-quality diet primarily based on healthy plant-based foods may be helpful prevent HF.</p>
</sec>
</abstract>
<kwd-group>
<kwd>cohort</kwd>
<kwd>epidemiology</kwd>
<kwd>heart failure</kwd>
<kwd>plant-based diet</kwd>
<kwd>risk factors</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This study was supported by Henan Medical Science and Technology Research Program Joint Construction Project (no. LHGJ20220277).</funding-statement>
</funding-group>
<counts>
<fig-count count="2"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="41"/>
<page-count count="8"/>
<word-count count="5802"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Nutritional Epidemiology</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec1">
<title>Introduction</title>
<p>Heart failure (HF) is a complex clinical syndrome characterized by structural and functional cardiac abnormalities that impair ventricular contraction or filling. This results in decreased cardiac output or increased intracardiac pressure, both at rest and during exercise, with primary symptoms including reduced exercise tolerance and fluid retention (<xref ref-type="bibr" rid="ref1">1</xref>). Globally, more than 56 million people are affected by HF (<xref ref-type="bibr" rid="ref2">2</xref>), and its prevalence has risen in part due to advances in treatment for other cardiac conditions such as myocardial infarction, valvular disease, and arrhythmias, which have extended patients&#x2019; lifespans (<xref ref-type="bibr" rid="ref3">3</xref>). However, hospitalizations and mortality due to HF continue to increase, with its global prevalence approaching epidemic levels (<xref ref-type="bibr" rid="ref4">4</xref>, <xref ref-type="bibr" rid="ref5">5</xref>). The high incidence and mortality rates, coupled with significant healthcare costs and a reduced quality of life, have made HF a substantial public health concern worldwide. HF is progressive, and once symptomatic HF develops, mortality risk can increase nearly nine-fold (<xref ref-type="bibr" rid="ref6">6</xref>). Individuals at risk or in the early stages of HF far outnumber those with diagnosed HF, emphasizing the importance of prevention. Despite advances in treatment, clinical interventions address only a fraction of HF care, highlighting the need for preventive strategies (<xref ref-type="bibr" rid="ref7">7</xref>).</p>
<p>In recent years, research has increasingly focused on dietary patterns in relation to chronic disease risk, aiming to capture the overall dietary intake and potential interactions among various food components. Plant-based diets, including the traditional Mediterranean and vegetarian diets, are typically characterized by high consumption of plant foods and minimal or no intake of animal products (<xref ref-type="bibr" rid="ref8">8</xref>). Evidence suggests that these diets&#x2014;often rich in fiber, vitamins, and bioactive compounds&#x2014;may reduce the risk of chronic diseases such as cardiovascular disease by mitigating oxidative stress and inflammation and providing neuroprotective effects (<xref ref-type="bibr" rid="ref9">9</xref>). However, not all plant-based foods are equally beneficial; for instance, foods like potatoes, refined sugars, and processed grains have been linked to a higher risk of chronic diseases. To distinguish among the quality of plant-based diets, researchers have developed three plant-based diet indices: the overall plant-based diet index (PDI), which emphasizes total plant food intake; the healthful plant-based diet index (hPDI), which highlights nutrient-dense plant foods such as whole grains, vegetables, nuts, legumes, coffee, and tea; and the unhealthful plant-based diet index (uPDI), which emphasizes less beneficial plant foods associated with increased chronic disease risk. Prior studies have found that adherence to a healthful plant-based diet that balances both beneficial and less beneficial plant-based foods, as well as animal foods, is significantly associated with a lower risk of type 2 diabetes, non-alcoholic fatty liver disease, frailty, and both all-cause and disease-specific mortality (<xref ref-type="bibr" rid="ref10 ref11 ref12 ref13">10&#x2013;13</xref>). However, there is limited evidence regarding the association between adherence to healthful plant-based dietary patterns and the risk of HF. Therefore, we conducted a large cohort study using data from the UK Biobank to evaluate the association between a healthful plant-based dietary pattern and HF risk.</p>
</sec>
<sec sec-type="methods" id="sec2">
<title>Methods</title>
<p>The UK Biobank is a large, prospective, population-based health study conducted worldwide that enrolled 500,000 participants aged 36&#x2013;73&#x202F;years between 2006 and 2010 (<xref ref-type="bibr" rid="ref14">14</xref>, <xref ref-type="bibr" rid="ref15">15</xref>). Participants completed comprehensive baseline assessments at 22 central assessment centers in England, Scotland, and Wales; further details of the study protocol have been described elsewhere (<xref ref-type="bibr" rid="ref16">16</xref>). The UK Biobank provides participants&#x2019; demographic characteristics, lifestyle, genetic information, blood samples and environmental exposure data, and tracks their health and medical records for decades afterwards. All participants provided written informed consent to participate, and ethical approval for the research involving humans was obtained from the NHS Northwest Multicenter Research Ethics Committee (no. 11/NW/0382).</p>
<p>We excluded participants without dietary assessment information, participants who withdrew consent during follow-up, participants with a diagnosis of HF at baseline. As a result, a total of 190,092 participants were included in the final analysis.</p>
<sec id="sec3">
<title>Assessment of HF</title>
<p>HF was identified through hospital inpatient records and death registry data, based on the International Classification of Diseases, 10th Revision (ICD-10), using codes I11.0, I13.0, I13.2, I50.0, I50.1, and I50.9 (<xref ref-type="bibr" rid="ref17">17</xref>). Data on hospital admissions extended up to October 2022 in England, August 2022 in Scotland, and May 2022 in Wales. Participants were monitored from the date of their visit to the assessment center until the first of these events: death, diagnosis of HF, or end of the follow-up period (October 2022 in England, August 2022 in Scotland, and May 2022 in Wales).</p>
</sec>
<sec id="sec4">
<title>Healthful plant-based dietary patterns</title>
<p>This study followed the previous research protocol and used the Oxford WebQ tool to record the average food intake over at least two 24-h periods, covering 200 common foods and 30 beverages (<xref ref-type="bibr" rid="ref18">18</xref>). Different scores were given based on the participants&#x2019; intake of healthful plant foods, unhealthful plant foods, and animal products to construct a hPDI and an uPDI (<xref ref-type="bibr" rid="ref19">19</xref>). The PDI consists of 17 food categories, including healthy plant-based foods (whole grains, fruits, vegetables, nuts, legumes, and vegetarian protein substitutes, as well as tea and coffee), unhealthy plant-based foods (fruit juices, refined grains, potatoes, sugary drinks, sweets and desserts), and animal-based foods (animal fats, dairy products, eggs, fish or seafood, meat, and other animal-derived foods) (<xref ref-type="bibr" rid="ref20">20</xref>). A complete list of food groups with examples is provided in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table S1</xref>. All of the above foods, except vegetable oils, can be used to calculate hPDI (<xref ref-type="bibr" rid="ref21">21</xref>). The 17 food groups were assigned quintile-based scores, with healthier options receiving positive scores (Q5&#x202F;=&#x202F;5, Q1&#x202F;=&#x202F;1) and unhealthy options receiving reverse scores. The hPDI was calculated by summing the positive scores for healthy plant foods and the reverse scores for unhealthy plant and animal foods. Conversely, the uPDI was derived using the opposite scoring approach (<xref ref-type="bibr" rid="ref22">22</xref>).</p>
</sec>
<sec id="sec5">
<title>Covariates</title>
<p>Covariates were selected <italic>a priori</italic>, mainly based on literature review (<xref ref-type="bibr" rid="ref16">16</xref>, <xref ref-type="bibr" rid="ref23">23</xref>). The following variables were included: demographic characteristics&#x2014;sex (male/female), age (years), education level (college/university vs. other), and employment status (employed/unemployed)&#x2014;along with other potential confounders associated with HF. These comprised body mass index (BMI, kg/m<sup>2</sup>), physical activity (PA) (low/moderate/high), alcohol consumption (never/previous/current), smoking status (never/previous/current), and history of chronic diseases, including cardiovascular disease (yes/no) and cancer (yes/no).</p>
</sec>
<sec id="sec6">
<title>Statistical analysis</title>
<p>Baseline continuous variables were summarized with means and standard deviations (SD), and categorical variables were described by counts and percentages. Missing data for covariates were handled with imputation using the &#x201C;mice&#x201D; package in R.</p>
<p>To examine HF risk across tertiles of various plant-based diet indices, Cox proportional hazards models were applied to calculate hazard ratios (HRs) with 95% confidence interval (CI). The plant-based diet indices was analyzed both categorically by tertile (using the lowest tertile as reference) and continuously as per 1-SD increment. Two models were used progressively: Model 1 was unadjusted; Model 2 adjusted for age, sex, Townsend deprivation index, PA, education, employment status, smoking, alcohol consumption, BMI, CVD and cancer. A restricted cubic spline was employed to explore the dose&#x2013;response relationship between continuous various plant-based diet indices and incident HF.</p>
<p>Subgroup analyses were conducted to assess if the association between plant-based diet indices and HF was influenced by age (&#x2264;65 or &#x003E;65&#x202F;years), sex (male or female), BMI (&#x003C;25 or &#x2265;25&#x202F;kg/m<sup>2</sup>), ethnicity (White or Others), education (college/university vs. other), PA (low or moderate/high), employment status, smoking status (never or ever), alcohol consumption (never or ever). Interaction terms (e.g., potential modifier &#x00D7; plant-based diet index) were introduced in Model 2 for each potential modifier.</p>
<p>Two sensitivity analyses were conducted to test the robustness of the findings: (1) excluding participants with fewer than 2&#x202F;years of follow-up, and (2) restricting the analysis to those with complete data (complete case analyses).</p>
</sec>
</sec>
<sec sec-type="results" id="sec7">
<title>Results</title>
<p>A total of 190,092 participants were included in the cohort, with a mean age of 56.42&#x202F;&#x00B1;&#x202F;7.94&#x202F;years, and 43.7% were female. During a mean follow-up of 13.04&#x202F;years, 4,351 incident HF cases were identified. Compared with participants without HF, those who developed HF were older, more likely to be male, less physically active, had lower educational attainment, and were more frequently unemployed. They were also more likely to be current smokers and had higher Townsend deprivation index scores and BMI (<xref ref-type="table" rid="tab1">Table 1</xref>). Baseline characteristics according to tertiles of hPDI, PDI, and uPDI scores are presented in <xref ref-type="supplementary-material" rid="SM1">Supplementary Tables S2&#x2013;S4</xref>.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Baseline characteristics of the participants included in this study.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Characteristics</th>
<th align="center" valign="top" rowspan="2">Total (<italic>n</italic>&#x202F;=&#x202F;190,092)</th>
<th align="center" valign="top" colspan="2">Incident heart failure</th>
<th align="center" valign="top" rowspan="2"><italic>p</italic></th>
</tr>
<tr>
<th align="center" valign="top">No (<italic>n</italic>&#x202F;=&#x202F;185,741)</th>
<th align="center" valign="top">Yes (<italic>n</italic>&#x202F;=&#x202F;4,351)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">BMI, kg/m<sup>2</sup></td>
<td align="char" valign="middle" char="(">26.91 (4.64)</td>
<td align="char" valign="middle" char="(">26.86 (4.61)</td>
<td align="char" valign="middle" char="(">29.09 (5.64)</td>
<td align="char" valign="top" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Age, y</td>
<td align="char" valign="middle" char="(">56.42 (7.94)</td>
<td align="char" valign="middle" char="(">56.28 (7.93)</td>
<td align="char" valign="middle" char="(">62.22 (6.13)</td>
<td align="char" valign="top" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Sex</td>
<td/>
<td/>
<td/>
<td align="char" valign="top" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Male</td>
<td align="char" valign="middle" char="(">106,938 (56.3)</td>
<td align="char" valign="middle" char="(">105,215 (56.6)</td>
<td align="char" valign="middle" char="(">1723 (39.6)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Female</td>
<td align="char" valign="middle" char="(">83,154 (43.7)</td>
<td align="char" valign="middle" char="(">80,526 (43.4)</td>
<td align="char" valign="middle" char="(">2,628 (60.4)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Ethnic</td>
<td/>
<td/>
<td/>
<td align="char" valign="top" char=".">0.002</td>
</tr>
<tr>
<td align="left" valign="middle">White</td>
<td align="char" valign="middle" char="(">181,036 (95.2)</td>
<td align="char" valign="middle" char="(">176,849 (95.2)</td>
<td align="char" valign="middle" char="(">4,187 (96.2)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Others</td>
<td align="char" valign="middle" char="(">9,056 (4.8)</td>
<td align="char" valign="middle" char="(">8,892 (4.8)</td>
<td align="char" valign="middle" char="(">164 (3.8)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Education</td>
<td/>
<td/>
<td/>
<td align="char" valign="top" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">College or university</td>
<td align="char" valign="middle" char="(">109,547 (57.6)</td>
<td align="char" valign="middle" char="(">106,598 (57.4)</td>
<td align="char" valign="middle" char="(">2,949 (67.8)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Other</td>
<td align="char" valign="middle" char="(">80,545 (42.4)</td>
<td align="char" valign="middle" char="(">79,143 (42.6)</td>
<td align="char" valign="middle" char="(">1,402 (32.2)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Employment</td>
<td/>
<td/>
<td/>
<td align="char" valign="top" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Yes</td>
<td align="char" valign="middle" char="(">72,443 (38.1)</td>
<td align="char" valign="middle" char="(">69,748 (37.6)</td>
<td align="char" valign="middle" char="(">2,695 (61.9)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">No</td>
<td align="char" valign="middle" char="(">117,649 (61.9)</td>
<td align="char" valign="middle" char="(">115,993 (62.4)</td>
<td align="char" valign="middle" char="(">1,656 (38.1)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Physical activity</td>
<td/>
<td/>
<td/>
<td align="char" valign="top" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">High</td>
<td align="char" valign="middle" char="(">34,941 (18.4)</td>
<td align="char" valign="middle" char="(">34,020 (18.3)</td>
<td align="char" valign="middle" char="(">921 (21.2)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Moderate</td>
<td align="char" valign="middle" char="(">80,215 (42.2)</td>
<td align="char" valign="middle" char="(">78,404 (42.2)</td>
<td align="char" valign="middle" char="(">1811 (41.6)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Low</td>
<td align="char" valign="middle" char="(">74,936 (39.4)</td>
<td align="char" valign="middle" char="(">73,317 (39.5)</td>
<td align="char" valign="middle" char="(">1,619 (37.2)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Smoke</td>
<td/>
<td/>
<td/>
<td align="char" valign="top" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Never</td>
<td align="char" valign="middle" char="(">108,457 (57.1)</td>
<td align="char" valign="middle" char="(">106,519 (57.3)</td>
<td align="char" valign="middle" char="(">1938 (44.5)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Previous</td>
<td align="char" valign="middle" char="(">66,730 (35.1)</td>
<td align="char" valign="middle" char="(">64,839 (34.9)</td>
<td align="char" valign="middle" char="(">1891 (43.5)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Current</td>
<td align="char" valign="middle" char="(">14,905 (7.8)</td>
<td align="char" valign="middle" char="(">14,383 (7.7)</td>
<td align="char" valign="middle" char="(">522 (12.0)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Drink</td>
<td/>
<td/>
<td/>
<td align="char" valign="top" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Never</td>
<td align="char" valign="middle" char="(">6,213 (3.3)</td>
<td align="char" valign="middle" char="(">6,042 (3.3)</td>
<td align="char" valign="middle" char="(">171 (3.9)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Previous</td>
<td align="char" valign="middle" char="(">5,680 (3.0)</td>
<td align="char" valign="middle" char="(">5,459 (2.9)</td>
<td align="char" valign="middle" char="(">221 (5.1)</td>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Current</td>
<td align="char" valign="middle" char="(">178,199 (93.7)</td>
<td align="char" valign="middle" char="(">174,240 (93.8)</td>
<td align="char" valign="middle" char="(">3,959 (91.0)</td>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Values are mean &#x00B1; SD, <italic>n</italic> (%), or median (IQR). BMI, body mass index.</p>
</table-wrap-foot>
</table-wrap>
<p>The relationship between plant-based diet indices and incident HF is depicted in <xref ref-type="table" rid="tab2">Table 2</xref> and <xref ref-type="fig" rid="fig1">Figure 1</xref>. Compared to the lowest tertile, multivariable-adjusted HRs of HF in the highest tertile were 0.94 (0.88&#x2013;1.02) for overall PDI, 0.84 (0.78&#x2013;0.91) for hPDI, and 1.11 (1.03&#x2013;1.19) for uPDI, respectively. Dose&#x2013;response analysis also confirmed that the PDI risk ratio consistently remained close to 1, indicating no significant dose&#x2013;response trend and no significant association with HF risk. However, hPDI showed a negative dose&#x2013;response relationship with HF risk, meaning higher scores were associated with lower risk; while uPDI showed a positive dose&#x2013;response relationship, with higher scores associated with higher risk (<xref ref-type="fig" rid="fig1">Figure 1</xref>).</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Associations of plant-based diet and incident heart failure.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Plant-based diet indices</th>
<th align="center" valign="top" rowspan="2">Case/Pearson-years</th>
<th align="center" valign="top" colspan="2">Model<sup>a</sup></th>
<th align="center" valign="top" colspan="2">Model<sup>b</sup></th>
</tr>
<tr>
<th align="center" valign="top">HR (95% CI)</th>
<th align="center" valign="top"><italic>P</italic></th>
<th align="center" valign="top">HR (95% CI)</th>
<th align="center" valign="top"><italic>P</italic></th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" colspan="6">PDI</td>
</tr>
<tr>
<td align="left" valign="top">T1</td>
<td align="center" valign="middle">1701/940151</td>
<td align="center" valign="middle">Ref</td>
<td/>
<td align="center" valign="middle">Ref</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">T2</td>
<td align="center" valign="middle">1461/818712</td>
<td align="center" valign="middle">0.98 (0.92&#x2013;1.06)</td>
<td align="char" valign="middle" char=".">0.6603</td>
<td align="center" valign="middle">1 (0.93&#x2013;1.08)</td>
<td align="char" valign="middle" char=".">0.9457</td>
</tr>
<tr>
<td align="left" valign="top">T3</td>
<td align="center" valign="middle">1189/719830</td>
<td align="center" valign="middle">0.91 (0.84&#x2013;0.98)</td>
<td align="char" valign="middle" char=".">0.0126</td>
<td align="center" valign="middle">0.94 (0.88&#x2013;1.02)</td>
<td align="char" valign="middle" char=".">0.1228</td>
</tr>
<tr>
<td align="left" valign="top">Per SD increase</td>
<td align="center" valign="middle">/</td>
<td align="center" valign="middle">0.96 (0.93&#x2013;0.99)</td>
<td align="char" valign="middle" char=".">0.0077</td>
<td align="center" valign="middle">0.97 (0.94&#x2013;1)</td>
<td align="char" valign="middle" char=".">0.0715</td>
</tr>
<tr>
<td align="left" valign="top" colspan="6">hPDI</td>
</tr>
<tr>
<td align="left" valign="top">T1</td>
<td align="center" valign="middle">1857/941198</td>
<td align="center" valign="middle">Ref</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">T2</td>
<td align="center" valign="middle">1252/727758</td>
<td align="center" valign="middle">0.87 (0.81&#x2013;0.94)</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
<td align="center" valign="middle">0.88 (0.82&#x2013;0.94)</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="top">T3</td>
<td align="center" valign="middle">1242/809737</td>
<td align="center" valign="middle">0.78 (0.72&#x2013;0.83)</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
<td align="center" valign="middle">0.84 (0.78&#x2013;0.91)</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="top">Per SD increase</td>
<td/>
<td align="center" valign="middle">0.9 (0.87&#x2013;0.93)</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
<td align="center" valign="middle">0.91 (0.88&#x2013;0.94)</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="top" colspan="6">uPDI</td>
</tr>
<tr>
<td align="left" valign="top">T1</td>
<td align="center" valign="middle">1531/859663</td>
<td align="center" valign="middle">Ref</td>
<td/>
<td align="center" valign="middle">Ref</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">T2</td>
<td align="center" valign="middle">1497/864791</td>
<td align="center" valign="middle">0.97 (0.91&#x2013;1.05)</td>
<td align="char" valign="middle" char=".">0.4573</td>
<td align="center" valign="middle">1 (0.94&#x2013;1.08)</td>
<td align="char" valign="middle" char=".">0.8912</td>
</tr>
<tr>
<td align="left" valign="top">T3</td>
<td align="center" valign="middle">1323/754240</td>
<td align="center" valign="middle">0.99 (0.92&#x2013;1.06)</td>
<td align="char" valign="middle" char=".">0.7371</td>
<td align="center" valign="middle">1.11 (1.03&#x2013;1.19)</td>
<td align="char" valign="middle" char=".">0.008</td>
</tr>
<tr>
<td align="left" valign="top">Per SD increase</td>
<td align="center" valign="middle">/</td>
<td align="center" valign="middle">0.99 (0.96&#x2013;1.02)</td>
<td align="char" valign="middle" char=".">0.6522</td>
<td align="center" valign="middle">1.06 (1.03&#x2013;1.09)</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><sup>a</sup>Original model without adjusting for any variables. <sup>b</sup>Adjusted for age and sex, PA, Townsend deprivation index, education, employment, smoking, drinking, BMI, CVD, and cancer. PDI, plant-based diet index; hPDI, healthy plant-based diet index; uPDI, unhealthful plant-based diet index; Ref, references.</p>
</table-wrap-foot>
</table-wrap>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Dose&#x2013;Response Relationship of PDI and hPDI, and uPDI With HF Incidence. <bold>(A)</bold> The dose&#x2013;response relationship of the PDI with HF incidence. <bold>(B)</bold> The dose&#x2013;response relationship of the hPDI with HF incidence. <bold>(C)</bold> The dose&#x2013;response relationship of the uPDI with HF incidence. PDI, the overall plant-based diet index, hPDI, healthful plant-based diet index, uPDI, and unhealthful plant-based diet index, HF, heart failure.</p>
</caption>
<graphic xlink:href="fnut-13-1769535-g001.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Three line charts display hazard ratios (HR; ninety-five percent confidence intervals) for PDI, hPDI, and uPDI. Each plot uses a solid red line with a shaded area for confidence intervals and a dashed black reference line at HR equals one. Chart A shows a mostly flat trend for PDI, B shows a decreasing HR for increasing hPDI, and C shows an increasing HR for higher uPDI.</alt-text>
</graphic>
</fig>
<p>In subgroup analyses, the overall PDI was not significantly associated with HF risk, except for a potential interaction by race. In contrast, adherence to a hPDI was consistently inversely associated with HF risk, with a stronger protective effect observed among participants aged &#x2264;65&#x202F;years. The uPDI was positively associated with HF risk overall, with a more pronounced association among current smokers. No other significant subgroup interactions were observed (<xref ref-type="fig" rid="fig2">Figure 2</xref>). These subgroup findings should be interpreted cautiously, as they are exploratory and hypothesis-generating (<xref ref-type="fig" rid="fig2">Figure 2</xref>). Sensitivity analyses confirmed the robustness of the findings regarding the associations between plant-based diet indices and incident HF (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table S5</xref>).</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>HR (95% CI) for HF comparing PDI and hPDI, and uPDI by selected characteristics. <bold>(A)</bold> Subgroup analysis of the associations of PDI with risk of HF. <bold>(B)</bold> Subgroup analysis of the associations of hPDI with risk of HF. <bold>(C)</bold> Subgroup analysis of the associations of uPDI with risk of HF. Forest plots showed HR and 95% CI for the highest category compared with the lowest category. All HRs and 95% CIs were estimated using Cox proportional hazard models with adjustment for sex, age, PA, education, employment, smoking, drinking, Townsend deprivation index, BMI, CVD, and cancer. BMI, body mass index; PA, physical activity.</p>
</caption>
<graphic xlink:href="fnut-13-1769535-g002.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Three forest plots labeled A, B, and C compare hazard ratios and confidence intervals for various health risk subgroups, including sex, age, ethnicity, education, physical activity, employment, smoking, drinking, and body mass index. Each panel lists subgroups along with case and person-year counts, their corresponding hazard ratios with confidence intervals, p-values, and interaction p-values. Panel A has hazard ratios clustered around one, while B shows lower ratios and C shows varied elevated risk. Red vertical dashed lines at one indicate the null value for hazard ratios, and horizontal lines represent confidence intervals for each subgroup point estimate.</alt-text>
</graphic>
</fig>
</sec>
<sec sec-type="discussion" id="sec8">
<title>Discussion</title>
<p>This study found that adherence to healthful plant-based diets was associated with a lower risk of HF, whereas intake of unhealthful plant-based diets were associated with a higher risk of HF. These associations were independent of lifestyle, sociodemographic characteristics, and multiple other risk factors.</p>
<p>In recent years, more and more studies have begun to focus on the relationship between dietary patterns and HF. Although the guidelines have not yet recommended a specific dietary pattern, there is currently more data supporting the Dietary Approaches to Stop Hypertension (DASH) diet and the Mediterranean diet. Studies have shown that the Mediterranean diet was significantly associated with lower risk of HF, especially in women, and that the diets were associated with lower levels of specific biomarkers such as NT-proBNP, a marker associated with HF (<xref ref-type="bibr" rid="ref24">24</xref>, <xref ref-type="bibr" rid="ref25">25</xref>). Mediterranean diet delays ventricular remodeling and delays the progression of HF (<xref ref-type="bibr" rid="ref26">26</xref>). However, only a few studies have investigated the association between plant-based diets and HF.</p>
<p>Previous studies have shown that PDI is inversely associated with the risk of CVD (<xref ref-type="bibr" rid="ref27 ref28 ref29 ref30 ref31">27&#x2013;31</xref>). People often maintain cardiovascular health by reducing animal-based diets and increasing plant-based diets but rarely consider the quality of the plant foods they eat. In the present study, no significant association was observed between the overall PDI and incident HF. This finding may reflect the heterogeneous nature of plant-based diets, as the overall PDI captures the quantity of plant-derived food intake without distinguishing between healthful and unhealthful plant foods. Consequently, the potential cardioprotective effects of nutrient-dense plant foods may be offset by adverse effects associated with refined grains, added sugars, and other unhealthful plant-based foods, resulting in an overall null association. In contrast, the healthful and unhealthful plant-based diet indices explicitly incorporate diet quality and more accurately capture meaningful differences in dietary patterns. These results suggest that diet quality, rather than plant-based intake per se, may be more relevant to HF risk. The PDI only reflects the ratio of plant-based foods to animal-based foods consumed, without distinguishing the quality of plant-based foods. A PDI score may include both a large amount of healthy and unhealthy plant-based foods, and their combined effects are neutralized. Not all plant-based diets are beneficial for cardiovascular disease, and some types of plant-based diets may cause more harm (<xref ref-type="bibr" rid="ref32">32</xref>). A healthy plant-based diet rich in dietary fiber, antioxidants, unsaturated fatty acids, and micronutrients may reduce the risk of HF through multiple mechanisms (<xref ref-type="bibr" rid="ref33 ref34 ref35">33&#x2013;35</xref>). Previous studies have shown that dietary fiber is associated with lower levels of inflammatory markers, while antioxidants can improve oxidative stress in the body to improve endothelial function (<xref ref-type="bibr" rid="ref36">36</xref>). Choosing a diet rich in unsaturated fatty acids was significantly associated with improve blood lipid markers and anti-inflammatory effects (<xref ref-type="bibr" rid="ref37">37</xref>). These ingredients all help control weight, improve insulin resistance, lower blood lipids, reduce inflammation, and promote more favorable diet-gut microbiome interactions, thereby reducing HF risk. In addition, long-term adherence to a healthful plant-based diet was associated with improve intestinal flora. Studies have confirmed that long-term healthful plant-based diet is associated with a lower relative abundance of streptococcus peptic ulcer, which is negatively correlated with high-density lipoprotein cholesterol (<xref ref-type="bibr" rid="ref38 ref39 ref40">38&#x2013;40</xref>). However, unhealthful plant-based diets are often low in fiber, poor in micronutrients, overly processed, and energy-dense, which may adversely affect the above pathways and are associated with an increased risk of overall HF. After fully adjusting for variables, participants who adhered to the plant-based dietary pattern had a lower risk of HF than those with the lowest adherence rate, while participants who consumed more unhealthy plant-based diets had a higher risk of HF than those who consumed less unhealthy plant-based diets. Dose&#x2013;response analysis revealed a consistent monotonic increase in HF risk with higher levels of uPDI, but a lower risk for higher hPDI. This finding suggests that patients with risk factors for HF need to consider whether their plant-based diet is healthy.</p>
<p>In this study, we also conducted a series of sensitivity analyses to ensure the robustness of our findings. Furthermore, to consider the diversity of diets, we calculated dietary scores instead of single nutrients. This is consistent with 2021 Dietary Guidance to Improve Cardiovascular Health, which recommend a more overall healthy eating pattern rather than individual nutrients (<xref ref-type="bibr" rid="ref41">41</xref>). To assess the robustness of our findings, we conducted extensive sensitivity analyses addressing potential residual confounding and reverse causation. The consistent, dose-dependent relationships observed, where higher hPDI was linearly associated with lower HF risk, and higher uPDI with elevated risk, suggesting that the associations are unlikely to be fully explained by unmeasured confounders, as residual confounding typically does not produce such graded, monotonic response patterns. Furthermore, the stability of these associations across nearly all subgroups in stratified analyses, the observed consistency, and their generalizability, and reduces the likelihood that they are driven by confounding specific to certain populations. To mitigate reverse causality, we performed analyses excluding participants with early-onset HF or major dietary changes within the first two years of follow-up. The persistence of significant associations in these sensitivity analyses suggests that pre-existing undiagnosed disease is unlikely to be the primary driver of our results.</p>
<p>Although this study is a large sample with comprehensive data on diet, risk factors, and confounders of HF risk, it has several limitations. First, the dietary intake was self-reported via a 24-h online questionnaire, which may not be representative of long-term dietary habits and may cause measurement errors. To improve reliability, participants with only a single recall were excluded, and the mean intake was calculated for those with two or more assessments. In addition, residual measurement error remains possible, but it is likely non-differential with respect to incident HF and would tend to attenuate, rather than exaggerate, the observed associations. Second, we did not differentiate between HF subtypes (e.g., HF with preserved vs. reduced ejection fraction) in our analysis. Therefore, the observed associations pertain to overall incident HF, and it remains unclear whether similar relationships exist for specific HF phenotypes. Future studies with detailed HF subtype data are warranted to explore these associations further. Third, even though we have adjusted for a wide range of covariates, residual or unknown confounding could not be ruled out because of the observational study design. Forth, although the prospective design reduces the likelihood of reverse causation, it remains possible that subclinical or undiagnosed conditions at baseline influenced dietary patterns. Sensitivity analyses excluding participants who developed new-onset HF within 2&#x202F;year of completing the last 24-h dietary recall produced similar results, supporting the robustness of our findings. Nevertheless, these limitations should be considered when interpreting the results. Finally, subgroup analyses were conducted to explore potential effect modification by sex, age, and other baseline characteristics. These analyses were not prespecified as primary hypotheses and should therefore be considered exploratory. Observed differences across subgroups are hypothesis-generating and may help guide future research, but they should be interpreted with caution and cannot be considered confirmatory.</p>
</sec>
<sec sec-type="conclusions" id="sec9">
<title>Conclusion</title>
<p>Our research found that adhering to a healthy plant-based dietary pattern inversely associated with the incidence of HF, whereas indicators of an unhealthy plant-based diet were positively associated with HF risk. These findings suggest that a healthy plant-based diet may represent a higher-quality dietary pattern in relation to HF risk. While causality cannot be inferred, adherence to an overall high-quality dietary pattern may be relevant from a public health perspective. Our results are consistent with existing dietary guidelines that emphasize greater intake of healthy plant-based foods and reduced consumption of unhealthy plant-based foods in populations at risk of HF.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec10">
<title>Data availability statement</title>
<p>The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/<xref ref-type="supplementary-material" rid="SM1">Supplementary material</xref>.</p>
</sec>
<sec sec-type="ethics-statement" id="sec11">
<title>Ethics statement</title>
<p>All participants provided written informed consent to participate and ethical approval for the research involving humans was obtained from the NHS Northwest Multicenter Research Ethics Committee (no. 11/NW/0382). The studies were conducted in accordance with the local legislation and institutional requirements. 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 sec-type="author-contributions" id="sec12">
<title>Author contributions</title>
<p>X-XC: Writing &#x2013; original draft. Y-JZ: Writing &#x2013; review &#x0026; editing, Methodology, Supervision, Data curation. W-LC: Project administration, Supervision, Writing &#x2013; review &#x0026; editing, Conceptualization. Y-ML: Writing &#x2013; review &#x0026; editing.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>The UK Biobank data was utilized under application no. 93398. We thank the participants and staff for their dedication and contribution.</p>
</ack>
<sec sec-type="COI-statement" id="sec13">
<title>Conflict of interest</title>
<p>The author(s) declared that this work 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="sec14">
<title>Generative AI statement</title>
<p>The author(s) declared that Generative AI was not 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="sec15">
<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="sec16">
<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.2026.1769535/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fnut.2026.1769535/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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<fn-group>
<fn fn-type="custom" custom-type="edited-by" id="fn0001"><p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1197939/overview">Emilia Ruggiero</ext-link>, Mediterranean Neurological Institute Neuromed (IRCCS), Italy</p></fn>
<fn fn-type="custom" custom-type="reviewed-by" id="fn0002"><p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2569847/overview">Simona Esposito</ext-link>, Mediterranean Neurological Institute Neuromed (IRCCS), Italy</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3266866/overview">Leonardo Lubis</ext-link>, Padjadjaran University, Indonesia</p></fn>
</fn-group>
<fn-group>
<fn fn-type="abbr" id="abbrev1"><label>Abbreviations:</label><p>HF, Heart failure; PDI, Plant-based diet index; hPDI, Healthful plant-based diet index; uPDI, Unhealthful plant-based diet index; CI, Confidence interval; HRs, Hazard ratios; SD, Standard deviations; CVD, Cardiovascular disease; BMI, Body mass index; PA, Physical activity; DASH, Dietary Approaches to Stop Hypertension.</p></fn>
</fn-group>
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</article>