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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.2025.1658775</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>Global burden of ischemic heart disease due to omega-3 deficiency: 204-country analysis, 1990&#x2013;2021</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Chen</surname>
<given-names>Xiaozhi</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn0004"><sup>&#x2020;</sup></xref>
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<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Chen</surname>
<given-names>Lei</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn0004"><sup>&#x2020;</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name>
<surname>Yang</surname>
<given-names>Xinyue</given-names>
</name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name>
<surname>Zhang</surname>
<given-names>Zhiqiang</given-names>
</name>
<xref rid="aff4" ref-type="aff"><sup>4</sup></xref>
<xref rid="aff5" ref-type="aff"><sup>5</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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<aff id="aff1"><label>1</label><institution>Department of Cardiology, National Cardiovascular Disease Regional Center for Anhui, The First Affiliated Hospital of Anhui Medical University</institution>, <city>Hefei, Anhui</city>, <country country="cn">China</country></aff>
<aff id="aff2"><label>2</label><institution>Department of Cardiology, Fujian Medical University Union Hospital</institution>, <city>Fuzhou, Fujian</city>, <country country="cn">China</country></aff>
<aff id="aff3"><label>3</label><institution>Department of Cardiology, Beijing Chaoyang Hospital, Capital Medical University</institution>, <city>Beijing</city>, <country country="cn">China</country></aff>
<aff id="aff4"><label>4</label><institution>Department of Cardiology, Tianjin Medical University General Hospital, Tianjin Medical University</institution>, <city>Tianjin</city>, <country country="cn">China</country></aff>
<aff id="aff5"><label>5</label><institution>Graduate School, Tianjin Medical University</institution>, <city>Tianjin</city>, <country country="cn">China</country></aff>
<author-notes><corresp id="c001"><label>&#x002A;</label>Correspondence: Zhiqiang Zhang, <email xlink:href="mailto:zzq23478@tmu.edu.cn">zzq23478@tmu.edu.cn</email>; Xinyue Yang, <email xlink:href="mailto:yangxinyue@tmu.edu.cn">yangxinyue@tmu.edu.cn</email></corresp><fn fn-type="equal" id="fn0004"><label>&#x2020;</label><p>These authors have contributed equally to this work</p></fn></author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2025-11-26">
<day>26</day>
<month>11</month>
<year>2025</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2025</year>
</pub-date>
<volume>12</volume>
<elocation-id>1658775</elocation-id>
<history>
<date date-type="received">
<day>04</day>
<month>07</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>30</day>
<month>10</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2025 Chen, Chen, Yang and Zhang.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Chen, Chen, Yang and Zhang</copyright-holder>
<license><ali:license_ref start_date="2025-11-26">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<sec id="sec1">
<title>Aim</title>
<p>This study evaluates the global burden, trends, and dietary risk factors of ischemic heart disease (IHD) from 1990 to 2021, focusing on socioeconomic and demographic variations.</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>The study analyzed IHD-related disability-adjusted life years (DALYs), age-standardized rates (ASR), age-standardized mortality rates (ASMR), and fatality counts. Temporal trends were assessed using estimated annual percentage changes (EAPCs). Dietary risk factors, such as seafood omega-3 fatty acid deficiency, were evaluated in relation to the socio-demographic index (SDI).</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>From 1990 to 2021, DALY rates and fatalities from IHD increased globally. Omega-3 fatty acid deficiencies were identified as a significant contributor. ASMR and age-standardized death rates (ASDR) rose most notably in Central Asia and Eastern Europe. Countries with lower SDI levels faced a higher IHD burden. National trends varied, with adverse correlations between IHD burden and SDI primarily linked to dietary risks.</p>
</sec>
<sec id="sec4">
<title>Conclusion</title>
<p>Deficiencies in omega-3 fatty acids and other dietary risks are key factors driving global IHD patterns. Public health strategies to improve diet, particularly in low- and middle-SDI regions, are essential to reducing the IHD burden.</p>
</sec>
</abstract>
<kwd-group>
<kwd>ischemic heart disease</kwd>
<kwd>Global Burden of Disease Study</kwd>
<kwd>diet low in seafood omega-3 fatty acids</kwd>
<kwd>socio-demographic index</kwd>
<kwd>disability-adjusted life years (DALYs)</kwd>
</kwd-group><funding-group><funding-statement>The author(s) declare that no financial support was received for the research and/or publication of this article.</funding-statement></funding-group>
<counts>
<fig-count count="5"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="72"/>
<page-count count="13"/>
<word-count count="8751"/>
</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="sec5">
<label>1</label>
<title>Introduction</title>
<p>Ischemic heart disease (IHD), characterized by left ventricular dysfunction&#x2014;either systolic or diastolic&#x2014;due to obstructive coronary artery disease (CAD), is a leading cause of premature death worldwide (<xref ref-type="bibr" rid="ref1">1</xref>). GBD study conceptualizes IHD as an aggregate of discrete sequelae, encompassing myocardial infarction (MI), stable angina (manifesting as chest pain), and ischemic cardiomyopathy (heart failure resulting from IHD) (<xref ref-type="bibr" rid="ref2">2</xref>, <xref ref-type="bibr" rid="ref3">3</xref>). This condition imposes substantial healthcare burdens at individual, national, and global levels. According to the American Heart Association, direct healthcare costs for cardiovascular disease increased from $103.5 billion (1996) to $251.4 billion (2018&#x2013;2021) (<xref ref-type="bibr" rid="ref4">4</xref>). Lifestyle factors including obesity, smoking, physical inactivity, and poor dietary habits increase the risk of developing IHD (<xref ref-type="bibr" rid="ref5 ref6 ref7">5&#x2013;7</xref>). Insufficient dietary intake of seafood-derived omega-3 fatty acids represents a significant risk factor. Omega-3 fatty acids, particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are essential polyunsaturated fatty acids with unique physiological functions (<xref ref-type="bibr" rid="ref8">8</xref>). EPA primarily exerts anti-inflammatory effects and improves blood lipid profiles, while DHA plays a critical role in myocardial cell membrane function and cardiac rhythm stability (<xref ref-type="bibr" rid="ref9">9</xref>). Studies have shown that daily intake of EPA and DHA can significantly reduce the risk of cardiovascular diseases (<xref ref-type="bibr" rid="ref10">10</xref>, <xref ref-type="bibr" rid="ref11">11</xref>). These marine-derived omega-3 fatty acids provide cardiovascular protection through multiple mechanisms, including: lowering blood cholesterol levels, reducing vascular inflammation, enhancing plaque stability, improving endothelial function, and maintaining cardiac cell membrane function (<xref ref-type="bibr" rid="ref9">9</xref>, <xref ref-type="bibr" rid="ref12">12</xref>).</p>
<p>This recommended dose can be achieved by regularly consuming omega-3-rich deep-sea fish, such as mackerel, salmon, and tuna (<xref ref-type="bibr" rid="ref13">13</xref>). However, global disparities in seafood consumption have resulted in inadequate omega-3 intake in many regions, contributing to an increased risk of cardiovascular diseases in affected populations (<xref ref-type="bibr" rid="ref14">14</xref>).</p>
<p>Research demonstrates that consumption of seafood-derived omega-3 fatty acids reduces blood cholesterol levels while providing multiple cardiovascular benefits, including decreased inflammation, enhanced plaque stability, and improved cellular membrane function, thereby reducing IHD incidence (<xref ref-type="bibr" rid="ref15">15</xref>). Over the past five decades, increasing seafood omega-3 fatty acid intake has emerged as a crucial strategy in preventing chronic cardiovascular disease (<xref ref-type="bibr" rid="ref16">16</xref>, <xref ref-type="bibr" rid="ref17">17</xref>).</p>
<p>Existing studies, often limited to specific countries or regions and short time spans, fail to fully capture the long-term impact of dietary seafood omega-3 deficiency on the global burden of IHD (<xref ref-type="bibr" rid="ref18">18</xref>, <xref ref-type="bibr" rid="ref19">19</xref>). This study analyzed recent GBD data to examine the global IHD burden attributable to insufficient seafood omega-3 fatty acid intake from 1990 to 2021, aiming to inform prevention strategies and dietary recommendations.</p>
<p>Research on gender and age stratification in IHD remains limited, with existing studies failing to fully capture the changing trends in IHD burden across different gender and age groups (<xref ref-type="bibr" rid="ref20">20</xref>, <xref ref-type="bibr" rid="ref21">21</xref>). This study addresses this gap by systematically evaluating the impact of dietary omega-3 fatty acid deficiency on the IHD burden across both gender and age groups.</p>
<p>Previous research on the relationship between omega-3 fatty acids and IHD has primarily focused on specific countries or small populations (<xref ref-type="bibr" rid="ref22">22</xref>, <xref ref-type="bibr" rid="ref23">23</xref>). In contrast, this study leverages the GBD database to comprehensively assess the effect of insufficient omega-3 fatty acid intake on IHD mortality and DALYs worldwide. By doing so, it provides a panoramic view of the global impact of this risk factor on cardiovascular health, offering valuable insights into its role in shaping IHD outcomes across diverse populations.</p>
<p>Beyond dietary intake, randomized trials and clinical guidance indicate preventive benefits of omega-3 supplementation for selected populations. For hypertriglyceridemia or high residual risk on statins, prescription EPA (e.g., icosapent ethyl 4&#x202F;g/day) reduced total ischemic events in REDUCE-IT, while VITAL suggested benefits particularly among individuals with low baseline fish intake. Professional society statements also endorse 1&#x2013;2 fish servings/week for primary prevention and higher, supervised doses for triglyceride lowering. These data contextualize our burden estimates and underscore the modifiability of omega-3&#x2013;related IHD risk (<xref ref-type="bibr" rid="ref10">10</xref>, <xref ref-type="bibr" rid="ref15">15</xref>, <xref ref-type="bibr" rid="ref24 ref25 ref26">24&#x2013;26</xref>).</p>
</sec>
<sec sec-type="materials|methods" id="sec6">
<label>2</label>
<title>Materials and methods</title>
<sec id="sec7">
<label>2.1</label>
<title>Data</title>
<p>A database from the GBD was used in this research.<xref ref-type="fn" rid="fn0001"><sup>1</sup></xref> The GBD 2021 incorporates the latest health surveys, including national dietary surveys, demographic data, and medical records, from an expanded number of countries and regions. These updates enhance the timeliness of the data by reflecting recent health trends and improve representativeness by capturing a broader range of populations and dietary patterns. This comprehensive integration strengthens the reliability of global health estimates and supports more accurate analyses of disease burden. From 1990 to 2021, 371 diseases and 88 risk factors from 204 countries and territories have been included in the database (<xref ref-type="bibr" rid="ref27">27</xref>). The GBD stratifies IHD burden according to sex, age, region, and country, utilizing the socio-demographic index (SDI). The SDI integrates three metrics: fertility rates among women under 25, educational attainment in populations over 15, and per capita income distribution. The GBD framework categorizes global data into 21 distinct geographical regions, including East Asia, Oceania, and Eastern Europe. IHD prevalence was evaluated through Bayesian meta-regression analysis. Omega-3 fatty acid deficiency is defined as daily consumption below 430&#x2013;470&#x202F;mg of combined eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) (<xref ref-type="bibr" rid="ref28">28</xref>).</p>
</sec>
<sec id="sec8">
<label>2.2</label>
<title>Estimation of IHD burden</title>
<p>The global IHD burden attributable to insufficient seafood omega-3 fatty acid intake was evaluated using mortality rates and DALYs, comprising years of life lost (YLL) and years lived with disability (YLD), from 1990 to 2021. All metrics, including ASMR and ASDR, were calculated per 100,000 population. Data were extracted using the GBD results tool.</p>
</sec>
<sec id="sec9">
<label>2.3</label>
<title>Case definitions and ascertainment in GBD</title>
<p>IHD was harmonized using standardized ICD codes (e.g., ICD-9410&#x2013;414; ICD-10 I20&#x2013;I25). Cause-of-death estimates were modeled in CODEm, with redistribution of &#x2018;garbage codes&#x2019; and covariate selection to address coding variation. Nonfatal IHD sequelae were synthesized via Bayesian meta-regression (DisMod-MR) with cross-walks for heterogeneous case definitions and adjustments for diagnostic practice changes (e.g., transition from ICD-9 to ICD-10). Verbal-autopsy inputs and surveillance data were incorporated where vital registration was sparse, improving cross-country comparability while propagating uncertainty intervals (<xref ref-type="bibr" rid="ref2">2</xref>, <xref ref-type="bibr" rid="ref3">3</xref>, <xref ref-type="bibr" rid="ref28">28</xref>).</p>
</sec>
<sec id="sec10">
<label>2.4</label>
<title>Statistical analysis</title>
<p>Age-standardized mortality rates (ASMR) and disability-adjusted life year rates (ASDR) were utilized to minimize demographic confounding. The EAPC formula, 100&#x202F;&#x00D7;&#x202F;(exp(<italic>&#x03B2;</italic>)&#x2212;1), incorporates the regression coefficient (&#x03B2;) derived from the linear regression of calendar year (X) (<xref ref-type="bibr" rid="ref29">29</xref>). ASR trend classifications were determined using confidence intervals (CIs). All statistical analyses were performed using R software (version 4.3.1).</p>
</sec>
</sec>
<sec sec-type="results" id="sec11">
<label>3</label>
<title>Results</title>
<sec id="sec12">
<label>3.1</label>
<title>IHD of the globally diet&#x2019;s lack in omega-3 fatty acids omega-3 from seafood, 1990&#x2013;2021</title>
<p>Globally in 2021, insufficient seafood omega-3 fatty acid intake contributed to 627,300 IHD deaths (95% UI: 119,500-1,082,700) and 15,511,000 DALYs (95% UI: 3,098,800-25,946,100) (<xref ref-type="table" rid="tab1">Table 1</xref>; <xref ref-type="fig" rid="fig1">Figures 1A</xref>,<xref ref-type="fig" rid="fig1">B</xref>).</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>The global ischemic heart disease burden attributable to diet low in seafood omega-3 fatty acids in 1990 and 2021 and the temporal trends from 1990 to 2021.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">characteristic</th>
<th align="center" valign="top" colspan="4">1990</th>
<th align="center" valign="top" colspan="4">2021</th>
<th align="center" valign="top" colspan="2">EAPC (1990&#x2013;2021)</th>
</tr>
<tr>
<th align="center" valign="top">Death cases, n&#x202F;&#x00D7;&#x202F;10<sup>3</sup> (95% UI)</th>
<th align="center" valign="top">ASMR per 10<sup>5</sup>, n (95% UI)</th>
<th align="center" valign="top">DALYs, n&#x202F;&#x00D7;&#x202F;10<sup>3</sup> (95% UI)</th>
<th align="center" valign="top">ASDR per 10<sup>5</sup>, n (95% UI)</th>
<th align="center" valign="top">Death cases, n&#x202F;&#x00D7;&#x202F;10<sup>3</sup> (95% UI)</th>
<th align="center" valign="top">ASMR per 10<sup>5</sup>, n (95% UI)</th>
<th align="center" valign="top">DALYs, n&#x202F;&#x00D7;&#x202F;10<sup>3</sup> (95% UI)</th>
<th align="center" valign="top">ASDR per 10<sup>5</sup>, n (95% UI)</th>
<th align="center" valign="top">ASMR, n (95% CI)</th>
<th align="center" valign="top">ASDR, n (95% CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Global</td>
<td align="char" valign="middle" char="(">500.2 (98.9&#x2013;839.6)</td>
<td align="char" valign="middle" char="(">13.9 (2.7&#x2013;23.6)</td>
<td align="char" valign="middle" char="(">13048.4 (2692.9&#x2013;21367.2)</td>
<td align="char" valign="middle" char="(">322.9 (65.8&#x2013;533.3)</td>
<td align="char" valign="middle" char="(">627.3 (119.5&#x2013;1082.7)</td>
<td align="char" valign="middle" char="(">7.5 (1.4&#x2013;12.9)</td>
<td align="char" valign="middle" char="(">15,511 (3098.8&#x2013;25946.1)</td>
<td align="char" valign="middle" char="(">181.1 (36.2&#x2013;302.8)</td>
<td align="char" valign="middle" char="(">&#x2212;2.21 (&#x2212;2.34&#x2212;2.08)</td>
<td align="char" valign="middle" char="(">&#x2212;2.11 (&#x2212;2.24&#x2212;1.97)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="11">Sex</td>
</tr>
<tr>
<td align="left" valign="middle">Male</td>
<td align="char" valign="middle" char="(">254.9 (50.7&#x2013;425.9)</td>
<td align="char" valign="middle" char="(">15.4 (3&#x2013;26.1)</td>
<td align="char" valign="middle" char="(">7408.7 (1541.2&#x2013;12173.8)</td>
<td align="char" valign="middle" char="(">379 (77.2&#x2013;626.5)</td>
<td align="char" valign="middle" char="(">324.9 (61.6&#x2013;559.6)</td>
<td align="char" valign="middle" char="(">8.5 (1.6&#x2013;14.7)</td>
<td align="char" valign="middle" char="(">8,875 (1805.7&#x2013;14856.3)</td>
<td align="char" valign="middle" char="(">216.4 (43.6&#x2013;363.5)</td>
<td align="char" valign="middle" char="(">&#x2212;2.12 (&#x2212;2.26&#x2212;1.98)</td>
<td align="char" valign="middle" char="(">&#x2212;2.05 (&#x2212;2.2&#x2212;1.91)</td>
</tr>
<tr>
<td align="left" valign="middle">Female</td>
<td align="char" valign="middle" char="(">245.3 (48.7&#x2013;417.4)</td>
<td align="char" valign="middle" char="(">12.4 (2.5&#x2013;21.4)</td>
<td align="char" valign="middle" char="(">5639.8 (1174.4&#x2013;9,324)</td>
<td align="char" valign="middle" char="(">266.5 (55&#x2013;442.6)</td>
<td align="char" valign="middle" char="(">302.5 (57.9&#x2013;520.8)</td>
<td align="char" valign="middle" char="(">6.5 (1.3&#x2013;11.2)</td>
<td align="char" valign="middle" char="(">6636.1 (1316.9&#x2013;11123.6)</td>
<td align="char" valign="middle" char="(">146.5 (29.2&#x2013;244.7)</td>
<td align="char" valign="middle" char="(">&#x2212;2.28 (&#x2212;2.4&#x2212;2.16)</td>
<td align="char" valign="middle" char="(">&#x2212;2.15 (&#x2212;2.27&#x2212;2.04)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="11">Socio-demographic index</td>
</tr>
<tr>
<td align="left" valign="middle">High SDI</td>
<td align="char" valign="middle" char="(">109.6 (20.2&#x2013;196.4)</td>
<td align="char" valign="middle" char="(">10.1 (1.9&#x2013;18)</td>
<td align="char" valign="middle" char="(">2202.5 (417.1&#x2013;3856.4)</td>
<td align="char" valign="middle" char="(">204.7 (38.9&#x2013;356.9)</td>
<td align="char" valign="middle" char="(">70.2 (13&#x2013;127.8)</td>
<td align="char" valign="middle" char="(">3.1 (0.6&#x2013;5.6)</td>
<td align="char" valign="middle" char="(">1357.9 (262.6&#x2013;2387.4)</td>
<td align="char" valign="middle" char="(">71.6 (14.3&#x2013;123.2)</td>
<td align="char" valign="middle" char="(">&#x2212;4.01 (&#x2212;4.12&#x2212;3.91)</td>
<td align="char" valign="middle" char="(">&#x2212;3.59 (&#x2212;3.68&#x2212;3.51)</td>
</tr>
<tr>
<td align="left" valign="middle">High-middle SDI</td>
<td align="char" valign="middle" char="(">128 (24.2&#x2013;219.7)</td>
<td align="char" valign="middle" char="(">15 (2.8&#x2013;26.1)</td>
<td align="char" valign="middle" char="(">3000.5 (589.8&#x2013;5032.7)</td>
<td align="char" valign="middle" char="(">312.3 (61&#x2013;526.2)</td>
<td align="char" valign="middle" char="(">118.5 (22.4&#x2013;213)</td>
<td align="char" valign="middle" char="(">6.2 (1.2&#x2013;11.1)</td>
<td align="char" valign="middle" char="(">2304.6 (460.3&#x2013;4001.7)</td>
<td align="char" valign="middle" char="(">120.6 (24.3&#x2013;208.5)</td>
<td align="char" valign="middle" char="(">&#x2212;3.39 (&#x2212;3.82&#x2212;2.96)</td>
<td align="char" valign="middle" char="(">&#x2212;3.73 (&#x2212;4.22&#x2212;3.24)</td>
</tr>
<tr>
<td align="left" valign="middle">Middle SDI</td>
<td align="char" valign="middle" char="(">123.3 (25.2&#x2013;203)</td>
<td align="char" valign="middle" char="(">13.7 (2.7&#x2013;22.9)</td>
<td align="char" valign="middle" char="(">3565.2 (755.8&#x2013;5752.1)</td>
<td align="char" valign="middle" char="(">322.4 (66.9&#x2013;527.8)</td>
<td align="char" valign="middle" char="(">194.5 (36.8&#x2013;338.1)</td>
<td align="char" valign="middle" char="(">7.9 (1.5&#x2013;13.9)</td>
<td align="char" valign="middle" char="(">4821.6 (964.1&#x2013;8042.5)</td>
<td align="char" valign="middle" char="(">179.8 (35.4&#x2013;302.4)</td>
<td align="char" valign="middle" char="(">&#x2212;1.78 (&#x2212;1.91&#x2212;1.65)</td>
<td align="char" valign="middle" char="(">&#x2212;1.97 (&#x2212;2.09&#x2212;1.85)</td>
</tr>
<tr>
<td align="left" valign="middle">Low-middle SDI</td>
<td align="char" valign="middle" char="(">104 (22&#x2013;170.4)</td>
<td align="char" valign="middle" char="(">17.7 (3.7&#x2013;29.7)</td>
<td align="char" valign="middle" char="(">3218.9 (713.7&#x2013;5148.4)</td>
<td align="char" valign="middle" char="(">466.5 (100.5&#x2013;756.5)</td>
<td align="char" valign="middle" char="(">178.3 (34.9&#x2013;297.4)</td>
<td align="char" valign="middle" char="(">13 (2.5&#x2013;21.9)</td>
<td align="char" valign="middle" char="(">5101.7 (1029.9&#x2013;8327.6)</td>
<td align="char" valign="middle" char="(">329.2 (65.5&#x2013;541.5)</td>
<td align="char" valign="middle" char="(">&#x2212;0.94 (&#x2212;1&#x2212;0.88)</td>
<td align="char" valign="middle" char="(">&#x2212;1.09 (&#x2212;1.14&#x2212;1.04)</td>
</tr>
<tr>
<td align="left" valign="middle">Low SDI</td>
<td align="char" valign="middle" char="(">34.4 (7.3&#x2013;57.6)</td>
<td align="char" valign="middle" char="(">16.2 (3.3&#x2013;27.5)</td>
<td align="char" valign="middle" char="(">1040.4 (230.7&#x2013;1727.7)</td>
<td align="char" valign="middle" char="(">414.1 (89.4&#x2013;691.9)</td>
<td align="char" valign="middle" char="(">65.2 (13.5&#x2013;109.2)</td>
<td align="char" valign="middle" char="(">13.9 (2.8&#x2013;23.8)</td>
<td align="char" valign="middle" char="(">1909.7 (409.5&#x2013;3115.5)</td>
<td align="char" valign="middle" char="(">336.7 (70.3&#x2013;559.7)</td>
<td align="char" valign="middle" char="(">&#x2212;0.47 (&#x2212;0.57&#x2212;0.37)</td>
<td align="char" valign="middle" char="(">&#x2212;0.75 (&#x2212;0.84&#x2212;0.66)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="11">Region</td>
</tr>
<tr>
<td align="left" valign="middle">Andean Latin America</td>
<td align="char" valign="middle" char="(">1.6 (0.3&#x2013;2.8)</td>
<td align="char" valign="middle" char="(">8.4 (1.6&#x2013;14.8)</td>
<td align="char" valign="middle" char="(">42.6 (9&#x2013;72.2)</td>
<td align="char" valign="middle" char="(">193.2 (39.4&#x2013;327.1)</td>
<td align="char" valign="middle" char="(">2.5 (0.5&#x2013;4.4)</td>
<td align="char" valign="middle" char="(">4.3 (0.8&#x2013;7.7)</td>
<td align="char" valign="middle" char="(">58 (11.3&#x2013;100.5)</td>
<td align="char" valign="middle" char="(">95.7 (18.4&#x2013;166.2)</td>
<td align="char" valign="middle" char="(">&#x2212;2.55 (&#x2212;2.84&#x2212;2.26)</td>
<td align="char" valign="middle" char="(">&#x2212;2.63 (&#x2212;2.92&#x2212;2.35)</td>
</tr>
<tr>
<td align="left" valign="middle">Australasia</td>
<td align="char" valign="middle" char="(">2.5 (0.4&#x2013;4.4)</td>
<td align="char" valign="middle" char="(">11.1 (2&#x2013;19.8)</td>
<td align="char" valign="middle" char="(">50.3 (9.1&#x2013;86.4)</td>
<td align="char" valign="middle" char="(">219.4 (40&#x2013;376.5)</td>
<td align="char" valign="middle" char="(">1.1 (0.2&#x2013;2.1)</td>
<td align="char" valign="middle" char="(">1.8 (0.3&#x2013;3.4)</td>
<td align="char" valign="middle" char="(">17.9 (3.4&#x2013;33.3)</td>
<td align="char" valign="middle" char="(">34 (6.6&#x2013;62)</td>
<td align="char" valign="middle" char="(">&#x2212;6.1 (&#x2212;6.26&#x2212;5.95)</td>
<td align="char" valign="middle" char="(">&#x2212;6.3 (&#x2212;6.51&#x2212;6.1)</td>
</tr>
<tr>
<td align="left" valign="middle">Caribbean</td>
<td align="char" valign="middle" char="(">4.1 (0.8&#x2013;7)</td>
<td align="char" valign="middle" char="(">16.8 (3.2&#x2013;28.7)</td>
<td align="char" valign="middle" char="(">102 (20.4&#x2013;170.2)</td>
<td align="char" valign="middle" char="(">388.2 (76.7&#x2013;651.3)</td>
<td align="char" valign="middle" char="(">5.2 (1&#x2013;9.2)</td>
<td align="char" valign="middle" char="(">9.6 (1.9&#x2013;17)</td>
<td align="char" valign="middle" char="(">129.4 (27.3&#x2013;222.4)</td>
<td align="char" valign="middle" char="(">242.4 (51.3&#x2013;416.3)</td>
<td align="char" valign="middle" char="(">&#x2212;1.97 (&#x2212;2.1&#x2212;1.84)</td>
<td align="char" valign="middle" char="(">&#x2212;1.66 (&#x2212;1.81&#x2212;1.51)</td>
</tr>
<tr>
<td align="left" valign="middle">Central Asia</td>
<td align="char" valign="middle" char="(">18.3 (3.8&#x2013;30.4)</td>
<td align="char" valign="middle" char="(">42.7 (8.7&#x2013;71.4)</td>
<td align="char" valign="middle" char="(">447.3 (96.2&#x2013;727)</td>
<td align="char" valign="middle" char="(">947.5 (201.5&#x2013;1,550)</td>
<td align="char" valign="middle" char="(">23.1 (4.5&#x2013;39.6)</td>
<td align="char" valign="middle" char="(">32.8 (6.2&#x2013;56.7)</td>
<td align="char" valign="middle" char="(">550.6 (111.2&#x2013;916.6)</td>
<td align="char" valign="middle" char="(">678.4 (134.2&#x2013;1146.6)</td>
<td align="char" valign="middle" char="(">&#x2212;1.42 (&#x2212;1.82&#x2212;1.03)</td>
<td align="char" valign="middle" char="(">&#x2212;1.77 (&#x2212;2.22&#x2212;1.32)</td>
</tr>
<tr>
<td align="left" valign="middle">Central Europe</td>
<td align="char" valign="middle" char="(">39.2 (7.6&#x2013;67)</td>
<td align="char" valign="middle" char="(">28.9 (5.6&#x2013;49.5)</td>
<td align="char" valign="middle" char="(">899.6 (182.5&#x2013;1494.6)</td>
<td align="char" valign="middle" char="(">625.3 (126.6&#x2013;1041.4)</td>
<td align="char" valign="middle" char="(">27 (4.9&#x2013;47.8)</td>
<td align="char" valign="middle" char="(">11.7 (2.2&#x2013;20.6)</td>
<td align="char" valign="middle" char="(">487.3 (90.6&#x2013;846.8)</td>
<td align="char" valign="middle" char="(">228.7 (43&#x2013;393.9)</td>
<td align="char" valign="middle" char="(">&#x2212;3.39 (&#x2212;3.57&#x2212;3.22)</td>
<td align="char" valign="middle" char="(">&#x2212;3.76 (&#x2212;3.94&#x2212;3.57)</td>
</tr>
<tr>
<td align="left" valign="middle">Central Latin America</td>
<td align="char" valign="middle" char="(">9.5 (1.9&#x2013;16.1)</td>
<td align="char" valign="middle" char="(">12.6 (2.5&#x2013;21.7)</td>
<td align="char" valign="middle" char="(">246.5 (50.5&#x2013;406.9)</td>
<td align="char" valign="middle" char="(">279.8 (56.2&#x2013;468.4)</td>
<td align="char" valign="middle" char="(">21.5 (4.1&#x2013;37.7)</td>
<td align="char" valign="middle" char="(">8.9 (1.7&#x2013;15.6)</td>
<td align="char" valign="middle" char="(">493.8 (100.4&#x2013;845.9)</td>
<td align="char" valign="middle" char="(">194.7 (39.4&#x2013;333.6)</td>
<td align="char" valign="middle" char="(">&#x2212;1.42 (&#x2212;1.67&#x2212;1.17)</td>
<td align="char" valign="middle" char="(">&#x2212;1.51 (&#x2212;1.78&#x2212;1.24)</td>
</tr>
<tr>
<td align="left" valign="middle">Central Sub-Saharan Africa</td>
<td align="char" valign="middle" char="(">2.2 (0.4&#x2013;4)</td>
<td align="char" valign="middle" char="(">11.4 (2.1&#x2013;21.1)</td>
<td align="char" valign="middle" char="(">62.4 (12.9&#x2013;116.3)</td>
<td align="char" valign="middle" char="(">263.9 (52.2&#x2013;487.7)</td>
<td align="char" valign="middle" char="(">4.9 (0.9&#x2013;8.9)</td>
<td align="char" valign="middle" char="(">10.6 (1.9&#x2013;19.3)</td>
<td align="char" valign="middle" char="(">142 (26.1&#x2013;257)</td>
<td align="char" valign="middle" char="(">238.9 (43.4&#x2013;433)</td>
<td align="char" valign="middle" char="(">&#x2212;0.61 (&#x2212;0.8&#x2212;0.41)</td>
<td align="char" valign="middle" char="(">&#x2212;0.69 (&#x2212;0.89&#x2212;0.5)</td>
</tr>
<tr>
<td align="left" valign="middle">East Asia</td>
<td align="char" valign="middle" char="(">58.2 (12&#x2013;96.9)</td>
<td align="char" valign="middle" char="(">8.7 (1.8&#x2013;14.6)</td>
<td align="char" valign="middle" char="(">1635.3 (349&#x2013;2711.9)</td>
<td align="char" valign="middle" char="(">188 (39.4&#x2013;312.2)</td>
<td align="char" valign="middle" char="(">76.9 (13.9&#x2013;140.8)</td>
<td align="char" valign="middle" char="(">4.2 (0.8&#x2013;7.7)</td>
<td align="char" valign="middle" char="(">1,545 (287.3&#x2013;2818.4)</td>
<td align="char" valign="middle" char="(">77.7 (14.5&#x2013;140)</td>
<td align="char" valign="middle" char="(">&#x2212;2.1 (&#x2212;2.55&#x2212;1.64)</td>
<td align="char" valign="middle" char="(">&#x2212;2.67 (&#x2212;3.06&#x2212;2.28)</td>
</tr>
<tr>
<td align="left" valign="middle">Eastern Europe</td>
<td align="char" valign="middle" char="(">51.9 (9.3&#x2013;91.8)</td>
<td align="char" valign="middle" char="(">21.3 (3.8&#x2013;37.7)</td>
<td align="char" valign="middle" char="(">1113.1 (212.4&#x2013;1938.8)</td>
<td align="char" valign="middle" char="(">423.9 (80.7&#x2013;738.9)</td>
<td align="char" valign="middle" char="(">48.9 (9.5&#x2013;90.7)</td>
<td align="char" valign="middle" char="(">13.9 (2.7&#x2013;25.6)</td>
<td align="char" valign="middle" char="(">924.3 (183.5&#x2013;1696.7)</td>
<td align="char" valign="middle" char="(">272.2 (54.2&#x2013;495.8)</td>
<td align="char" valign="middle" char="(">&#x2212;2.42 (&#x2212;3.18&#x2212;1.66)</td>
<td align="char" valign="middle" char="(">&#x2212;2.65 (&#x2212;3.49&#x2212;1.8)</td>
</tr>
<tr>
<td align="left" valign="middle">Eastern Sub-Saharan Africa</td>
<td align="char" valign="middle" char="(">6.1 (1.3&#x2013;10.4)</td>
<td align="char" valign="middle" char="(">8.7 (1.8&#x2013;14.5)</td>
<td align="char" valign="middle" char="(">187.6 (42.4&#x2013;312.5)</td>
<td align="char" valign="middle" char="(">223.1 (48.5&#x2013;377.3)</td>
<td align="char" valign="middle" char="(">11.9 (2.5&#x2013;19.7)</td>
<td align="char" valign="middle" char="(">7.6 (1.5&#x2013;12.9)</td>
<td align="char" valign="middle" char="(">358.8 (77.4&#x2013;590.3)</td>
<td align="char" valign="middle" char="(">184.7 (38.5&#x2013;306.2)</td>
<td align="char" valign="middle" char="(">&#x2212;0.65 (&#x2212;0.76&#x2212;0.53)</td>
<td align="char" valign="middle" char="(">&#x2212;0.88 (&#x2212;0.99&#x2212;0.77)</td>
</tr>
<tr>
<td align="left" valign="middle">High-income Asia Pacific</td>
<td align="char" valign="middle" char="(">0.6 (0.1&#x2013;1.2)</td>
<td align="char" valign="middle" char="(">0.3 (0.1&#x2013;0.7)</td>
<td align="char" valign="middle" char="(">12.1 (2.3&#x2013;24.9)</td>
<td align="char" valign="middle" char="(">6.3 (1.2&#x2013;13.2)</td>
<td align="char" valign="middle" char="(">0.2 (0&#x2013;0.4)</td>
<td align="char" valign="middle" char="(">0 (0&#x2013;0.1)</td>
<td align="char" valign="middle" char="(">2.2 (0.4&#x2013;5.3)</td>
<td align="char" valign="middle" char="(">0.5 (0.1&#x2013;1.2)</td>
<td align="char" valign="middle" char="(">&#x2212;8.01 (&#x2212;8.4&#x2212;7.63)</td>
<td align="char" valign="middle" char="(">&#x2212;8 (&#x2212;8.35&#x2212;7.65)</td>
</tr>
<tr>
<td align="left" valign="middle">High-income North America</td>
<td align="char" valign="middle" char="(">44 (8.1&#x2013;78.8)</td>
<td align="char" valign="middle" char="(">12.3 (2.3&#x2013;22)</td>
<td align="char" valign="middle" char="(">857.5 (160.6&#x2013;1491.4)</td>
<td align="char" valign="middle" char="(">252.1 (47.6&#x2013;436.9)</td>
<td align="char" valign="middle" char="(">38.3 (7.2&#x2013;69.4)</td>
<td align="char" valign="middle" char="(">5.7 (1.1&#x2013;10.2)</td>
<td align="char" valign="middle" char="(">760.5 (148.8&#x2013;1325.8)</td>
<td align="char" valign="middle" char="(">125.9 (25&#x2013;216)</td>
<td align="char" valign="middle" char="(">&#x2212;2.8 (&#x2212;2.99&#x2212;2.62)</td>
<td align="char" valign="middle" char="(">&#x2212;2.47 (&#x2212;2.64&#x2212;2.3)</td>
</tr>
<tr>
<td align="left" valign="middle">North Africa and Middle East</td>
<td align="char" valign="middle" char="(">51.4 (10.9&#x2013;84.7)</td>
<td align="char" valign="middle" char="(">33.6 (7&#x2013;56.4)</td>
<td align="char" valign="middle" char="(">1474.5 (322.5&#x2013;2400.3)</td>
<td align="char" valign="middle" char="(">804.8 (172.3&#x2013;1315.4)</td>
<td align="char" valign="middle" char="(">76.7 (15.2&#x2013;131.5)</td>
<td align="char" valign="middle" char="(">18.8 (3.6&#x2013;32.7)</td>
<td align="char" valign="middle" char="(">2061.2 (431&#x2013;3462.6)</td>
<td align="char" valign="middle" char="(">420.8 (85.1&#x2013;714.2)</td>
<td align="char" valign="middle" char="(">&#x2212;2.13 (&#x2212;2.2&#x2212;2.05)</td>
<td align="char" valign="middle" char="(">&#x2212;2.38 (&#x2212;2.45&#x2212;2.3)</td>
</tr>
<tr>
<td align="left" valign="middle">Oceania</td>
<td align="char" valign="middle" char="(">0.3 (0.1&#x2013;0.5)</td>
<td align="char" valign="middle" char="(">9.1 (1.8&#x2013;16.2)</td>
<td align="char" valign="middle" char="(">8.9 (1.8&#x2013;15.6)</td>
<td align="char" valign="middle" char="(">246.8 (49.6&#x2013;437.7)</td>
<td align="char" valign="middle" char="(">0.6 (0.1&#x2013;1.1)</td>
<td align="char" valign="middle" char="(">7.8 (1.3&#x2013;14.3)</td>
<td align="char" valign="middle" char="(">19.8 (3.8&#x2013;36)</td>
<td align="char" valign="top" char="(">211.9 (38.9&#x2013;380.4)</td>
<td align="char" valign="top" char="(">&#x2212;0.3 (&#x2212;0.53&#x2212;0.08)</td>
<td align="char" valign="top" char="(">&#x2212;0.28 (&#x2212;0.51&#x2212;0.06)</td>
</tr>
<tr>
<td align="left" valign="top">South Asia</td>
<td align="char" valign="top" char="(">111 (24.5&#x2013;181.6)</td>
<td align="char" valign="top" char="(">19.3 (4.1&#x2013;32.2)</td>
<td align="char" valign="top" char="(">3580.4 (821.3&#x2013;5736.5)</td>
<td align="char" valign="top" char="(">530.6 (118.6&#x2013;862.2)</td>
<td align="char" valign="top" char="(">214.3 (42.4&#x2013;359)</td>
<td align="char" valign="top" char="(">15.1 (2.9&#x2013;25.5)</td>
<td align="char" valign="top" char="(">6226.5 (1284.4&#x2013;10237.1)</td>
<td align="char" valign="top" char="(">391.1 (79.5&#x2013;647.9)</td>
<td align="char" valign="top" char="(">&#x2212;0.68 (&#x2212;0.76&#x2212;0.6)</td>
<td align="char" valign="top" char="(">&#x2212;0.92 (&#x2212;0.98&#x2212;0.86)</td>
</tr>
<tr>
<td align="left" valign="top">Southeast Asia</td>
<td align="char" valign="top" char="(">18.8 (3.6&#x2013;32.1)</td>
<td align="char" valign="top" char="(">7.8 (1.5&#x2013;13.6)</td>
<td align="char" valign="top" char="(">576 (117.8&#x2013;969.7)</td>
<td align="char" valign="top" char="(">198.6 (38.9&#x2013;337.2)</td>
<td align="char" valign="top" char="(">15 (2.9&#x2013;27.9)</td>
<td align="char" valign="top" char="(">2.5 (0.5&#x2013;4.7)</td>
<td align="char" valign="top" char="(">422.1 (86.4&#x2013;766.8)</td>
<td align="char" valign="top" char="(">61.4 (12.3&#x2013;112.7)</td>
<td align="char" valign="top" char="(">&#x2212;3.65 (&#x2212;3.87&#x2212;3.43)</td>
<td align="char" valign="top" char="(">&#x2212;3.8 (&#x2212;4&#x2212;3.6)</td>
</tr>
<tr>
<td align="left" valign="top">Southern Latin America</td>
<td align="char" valign="top" char="(">6.6 (1.3&#x2013;11.5)</td>
<td align="char" valign="top" char="(">15.6 (3&#x2013;27.1)</td>
<td align="char" valign="top" char="(">149.9 (30&#x2013;255)</td>
<td align="char" valign="top" char="(">331.2 (66.3&#x2013;564.8)</td>
<td align="char" valign="top" char="(">4.1 (0.8&#x2013;7.1)</td>
<td align="char" valign="top" char="(">4.6 (0.9&#x2013;7.9)</td>
<td align="char" valign="top" char="(">84.9 (16.1&#x2013;148.1)</td>
<td align="char" valign="top" char="(">99.7 (19.1&#x2013;173.7)</td>
<td align="char" valign="top" char="(">&#x2212;3.66 (&#x2212;3.83&#x2212;3.49)</td>
<td align="char" valign="top" char="(">&#x2212;3.66 (&#x2212;3.81&#x2212;3.5)</td>
</tr>
<tr>
<td align="left" valign="top">Southern Sub-Saharan Africa</td>
<td align="char" valign="top" char="(">2.3 (0.5&#x2013;3.8)</td>
<td align="char" valign="top" char="(">8.8 (1.9&#x2013;15.5)</td>
<td align="char" valign="top" char="(">66.3 (15&#x2013;110.1)</td>
<td align="char" valign="top" char="(">221.1 (48.9&#x2013;370.4)</td>
<td align="char" valign="top" char="(">4.8 (1&#x2013;8.1)</td>
<td align="char" valign="top" char="(">9.2 (1.8&#x2013;15.9)</td>
<td align="char" valign="top" char="(">131.7 (28.3&#x2013;218.1)</td>
<td align="char" valign="top" char="(">214.7 (45&#x2013;360.6)</td>
<td align="char" valign="top" char="(">0.05 (&#x2212;0.39&#x2013;0.49)</td>
<td align="char" valign="top" char="(">&#x2212;0.14 (&#x2212;0.59&#x2013;0.32)</td>
</tr>
<tr>
<td align="left" valign="top">Tropical Latin America</td>
<td align="char" valign="top" char="(">12.6 (2.5&#x2013;21.3)</td>
<td align="char" valign="top" char="(">14.9 (2.9&#x2013;25.4)</td>
<td align="char" valign="top" char="(">360 (75.5&#x2013;592.9)</td>
<td align="char" valign="top" char="(">364.3 (74.1&#x2013;610)</td>
<td align="char" valign="top" char="(">14.9 (2.9&#x2013;25.9)</td>
<td align="char" valign="top" char="(">5.9 (1.1&#x2013;10.2)</td>
<td align="char" valign="top" char="(">395.8 (77.9&#x2013;664.1)</td>
<td align="char" valign="top" char="(">151.4 (29.8&#x2013;254.6)</td>
<td align="char" valign="top" char="(">&#x2212;3.05 (&#x2212;3.13&#x2212;&#x2212;2.96)</td>
<td align="char" valign="top" char="(">-2.96 (&#x2212;3.04&#x2212;2.88)</td>
</tr>
<tr>
<td align="left" valign="top">Western Europe</td>
<td align="char" valign="top" char="(">51.3 (9.3&#x2013;92.2)</td>
<td align="char" valign="top" char="(">8.8 (1.6&#x2013;15.8)</td>
<td align="char" valign="top" char="(">975.6 (184.1&#x2013;1728.9)</td>
<td align="char" valign="top" char="(">174.9 (33.3&#x2013;307.5)</td>
<td align="char" valign="top" char="(">22.3 (4.1&#x2013;41.2)</td>
<td align="char" valign="top" char="(">2 (0.4&#x2013;3.6)</td>
<td align="char" valign="top" char="(">346.7 (66.5&#x2013;623.6)</td>
<td align="char" valign="top" char="(">37 (7.2&#x2013;65.7)</td>
<td align="char" valign="top" char="(">&#x2212;5.03 (&#x2212;5.16&#x2212;4.9)</td>
<td align="char" valign="top" char="(">&#x2212;5.19 (&#x2212;5.34&#x2212;5.04)</td>
</tr>
<tr>
<td align="left" valign="top">Western Sub-Saharan Africa</td>
<td align="char" valign="top" char="(">7.7 (1.6&#x2013;13.5)</td>
<td align="char" valign="top" char="(">10.2 (2&#x2013;18.1)</td>
<td align="char" valign="top" char="(">200.6 (41.8&#x2013;348)</td>
<td align="char" valign="top" char="(">224.1 (45.8&#x2013;390.9)</td>
<td align="char" valign="top" char="(">13.3 (2.8&#x2013;23.1)</td>
<td align="char" valign="top" char="(">8 (1.6&#x2013;14.1)</td>
<td align="char" valign="top" char="(">352.6 (77.9&#x2013;600.7)</td>
<td align="char" valign="top" char="(">171.1 (36&#x2013;295.4)</td>
<td align="char" valign="top" char="(">&#x2212;1.02 (&#x2212;1.22&#x2212;0.81)</td>
<td align="char" valign="top" char="(">&#x2212;1.13 (&#x2212;1.35&#x2212;0.91)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>ASMR, age-standardized mortality rate; ASDR, age-standardized disability-adjusted life year rate; EAPC, estimated annual percentage change.</p>
</table-wrap-foot>
</table-wrap>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Burden of IHD due to dietary deficiencies in seafood omega-3 fatty acids in the SDI region. Global IHD <bold>(A)</bold> deaths, <bold>(B)</bold> DALYs, <bold>(C)</bold> ASMR, and <bold>(D)</bold> ASDR attributable to physical activity at all ages from 1990 through 2021. 2021 Global <bold>(E)</bold> Deaths, <bold>(F)</bold> DALYs, <bold>(G)</bold> Mortality, and <bold>(H)</bold> DALYs IHD disaggregated by lack of age.</p>
</caption>
<graphic xlink:href="fnut-12-1658775-g001.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Eight-panel figure showing data on deaths, DAYs, ASMR, ASDR, and DALYs over time and across ages in SDI regions. Panels A and B show an increase in deaths and DALYs from 1990 to 2020. Panels C and D illustrate ASMR and ASDR trends, decreasing in most regions. Panels E and F depict deaths and DALYs by age, highest among older age groups. Panels G and H display increasing death and DALY rates with age. Different SDI regions are distinguished by color.</alt-text>
</graphic>
</fig>
<p>Age-standardized analysis revealed a declining IHD burden despite increasing absolute numbers (<xref ref-type="table" rid="tab1">Table 1</xref>). Since 1990, the absolute burden of IHD attributable to inadequate seafood omega-3 fatty acid intake has increased. The ASMR per 100,000 decreased from 13.9 (95% UI: 2.7&#x2013;23.6) in 1990 to 7.5 (95% UI: 1.4&#x2013;12.9) in 2021, with an EAPC of &#x2212;2.21 (95% CI: &#x2212;2.34 to &#x2212;2.08) (<xref ref-type="table" rid="tab1">Table 1</xref>; <xref ref-type="fig" rid="fig1">Figure 1C</xref>). The age-standardized DALY rate (ASDR) per 100,000 declined from 322.9 (95% UI: 65.8&#x2013;533.3) in 1990 to 181.1 (95% UI: 36.2&#x2013;302.8) in 2021, with an EAPC of &#x2212;2.11 (95% CI: &#x2212;2.24 to &#x2212;2.08) (<xref ref-type="table" rid="tab1">Table 1</xref>; <xref ref-type="fig" rid="fig1">Figure 1D</xref>).</p>
</sec>
<sec id="sec13">
<label>3.2</label>
<title>IHD burden by age and sex in diets deficient in omega-3 fatty acids from seafood</title>
<p>Between 1990 and 2021, IHD deaths attributable to insufficient seafood omega-3 intake increased from 254,900 (95% UI: 50.7&#x2013;425.9) to 324,900 (95% UI: 61.6&#x2013;559.6) in men, and from 245,300 (95% UI: 48,700-417,400) to 302,500 (95% UI: 57,900-520,800) in women. DALYs increased from 7,408,700 (95% UI: 1,541,200-12,173,800) to 8,875,000 (95% UI: 1,805,700-14,856,300) in men, and from 5,639,800 (95% UI: 1,174,400-9,324,000) to 6,636,100 (95% UI: 1,316,900-11,123,600) in women. The burden was consistently higher in men than women (<xref ref-type="table" rid="tab1">Table 1</xref>; <xref ref-type="fig" rid="fig2">Figures 2A</xref>,<xref ref-type="fig" rid="fig2">B</xref>).</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>IHD year-specific <bold>(A)</bold> deaths and death rates and <bold>(C)</bold> DALY, and age-specific <bold>(B)</bold> deaths and death rates and <bold>(D)</bold> DALY for IHD by sex.</p>
</caption>
<graphic xlink:href="fnut-12-1658775-g002.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Four bar graphs show data on deaths and disability-adjusted life years (DALYs) for males and females. Charts A and B depict trends from 1990 to 2020, with male figures higher. Charts C and D illustrate age distribution, showing an increase with age, with males generally higher. Error bars indicate variability in data.</alt-text>
</graphic>
</fig>
<p>ASMRs decreased from 15.4/100,000 (95% UI: 3&#x2013;26.1) to 8.5/100,000 (95% UI: 1.6&#x2013;14.7) in men [EAPC: &#x2212;2.12 (95% CI: &#x2212;2.26 to &#x2212;1.98)] and from 12.4/100,000 (95% UI: 2.5&#x2013;21.4) to 6.5/100,000 (95% UI: 1.3&#x2013;11.2) in women [EAPC: &#x2212;2.28 (95% CI: &#x2212;2.4 to &#x2212;2.16)]. ASDRs declined from 379/100,000 (95% UI: 77.2&#x2013;626.5) to 216.4/100,000 (95% UI: 43.6&#x2013;363.5) in men [EAPC: &#x2212;2.05 (95% CI: &#x2212;2.2 to &#x2212;1.91)] and from 266.5/100,000 (95% UI: 55&#x2013;442.6) to 146.5/100,000 (95% UI: 29.2&#x2013;244.7) in women [EAPC: &#x2212;2.15 (95% CI: &#x2212;2.2 to &#x2212;2.04)]. Age-standardized rates showed consistent declines for both sexes (<xref ref-type="table" rid="tab1">Table 1</xref>; <xref ref-type="fig" rid="fig2">Figures 2A</xref>,<xref ref-type="fig" rid="fig2">B</xref>).</p>
<p>Age-stratified analysis for 2021 revealed peak mortality and DALYs in the 75&#x2013;79 age group, with consistently higher burdens among men (<xref ref-type="table" rid="tab1">Table 1</xref>; <xref ref-type="fig" rid="fig1">Figures 1E</xref>,<xref ref-type="fig" rid="fig1">F</xref>; <xref ref-type="fig" rid="fig2">2C</xref>,<xref ref-type="fig" rid="fig2">D</xref>).</p>
</sec>
<sec id="sec14">
<label>3.3</label>
<title>By SDI region, the burden of IHD in diets lacking in omega-3 fatty acids from seafood</title>
<p>All five SDI quintiles showed decreasing IHD burden attributable to insufficient seafood omega-3 intake between 1990 and 2021. High SDI regions demonstrated the most substantial reductions, with EAPCs of &#x2212;4.01 (95% CI: &#x2212;4.12 to &#x2212;3.91) for ASMR and &#x2212;3.59 (95% CI: &#x2212;3.68 to &#x2212;3.51) for ASDR. Low SDI regions exhibited modest changes, with EAPCs of &#x2212;0.47 (95% CI: &#x2212;0.57 to &#x2212;0.37) for ASMR and &#x2212;0.75 (95% CI: &#x2212;0.84 to &#x2212;0.66) for ASDR (<xref ref-type="table" rid="tab1">Table 1</xref>).</p>
</sec>
<sec id="sec15">
<label>3.4</label>
<title>IHD burden by country and location in diets lacking in omega-3 fatty acids from seafood</title>
<p>Among 21 geographic regions in 2021, Central Asia showed the highest burden with an ASMR of 32.8/100,000 (95% UI: 6.2&#x2013;56.7) and ASDR of 678.4/100,000 (95% UI: 134.2&#x2013;1146.6). North Africa and Middle East followed with an ASMR of 18.8/100,000 (95% UI: 3.6&#x2013;32.7) and ASDR of 420.8/100,000 (95% UI: 85.1&#x2013;714.2). The lowest rates were observed in High-income Asia Pacific [ASMR: 0/100,000 (95% UI: 0&#x2013;0.1); ASDR: 0.5/100,000 (95% UI: 0.1&#x2013;1.2)] and Australasia [ASMR: 1.8/100,000 (95% UI: 0.3&#x2013;3.4); ASDR: 34/100,000 (95% UI: 6.6&#x2013;62)] (<xref ref-type="fig" rid="fig3">Figure 3</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Table S1</xref>).</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>Spatial distribution of IHD due to lack of physical activity in 2021. <bold>(A)</bold> ASMR, <bold>(B)</bold> EAPC of ASMR, <bold>(C)</bold> ASDR, and <bold>(D)</bold> EAPC of ASDR.</p>
</caption>
<graphic xlink:href="fnut-12-1658775-g003.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">World maps showing various health metrics with color coding for ASMR and ASDR per 100,000 people, and EAPC trends across different regions. Each panel (A, B, C, D) provides data for specific health statistics, highlighting areas like the Caribbean, Persian Gulf, and Northern Europe, among others. Insets focus on smaller regions with detailed color variations indicating different levels of each metric.</alt-text>
</graphic>
</fig>
<p>Southern Sub-Saharan Africa uniquely showed increasing trends [ASMR EAPC: 0.05 (95% CI: &#x2212;0.39 to 0.49); ASDR EAPC: &#x2212;0.14 (95% CI: &#x2212;0.59 to 0.32)]. Australasia and High-income Asia Pacific demonstrated the steepest declines among all other regions (<xref ref-type="fig" rid="fig3">Figure 3</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Table S1</xref>).</p>
<p>National-level analysis revealed stable trends in four countries (C&#x00F4;te d&#x2019;Ivoire, Kiribati, Niger, Uzbekistan) and significant increases (EAPC &#x003E; 2) in American Samoa, Lesotho, Nauru, and Northern Mariana Islands. The Republic of Korea showed the largest decrease (ASMR EAPC &#x003C; &#x2212;8). The highest death counts were observed in China [72,410,200 (95% UI: 13,118,600&#x2013;133,501,900)], USA [36,886,200 (95% UI: 6,932,300&#x2013;66,672,000)], and Pakistan [29,989,800 (95% UI: 6,481,200&#x2013;52,583,600)]. India led in DALYs [5,066,234,400 (95% UI: 1,041,340,000&#x2013;8,314,562,100)], followed by China [1,428,781,500 (95% UI: 265,229,100&#x2013;2,626,045,200)] and Pakistan [942,733,100 (95% UI: 210,904,600&#x2013;1,619,260,200)] (<xref ref-type="fig" rid="fig3">Figure 3</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Table S1</xref>).</p>
<p>Age-stratified analysis for 2021 showed increasing death and DALY rates with age, peaking after 80&#x202F;years across all locations (<xref ref-type="fig" rid="fig1">Figures 1G</xref>,<xref ref-type="fig" rid="fig1">H</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Figures S1, S2</xref>).</p>
</sec>
<sec id="sec16">
<label>3.5</label>
<title>Correlation between ASMR, ASDR and SDI values for IHD</title>
<p>SDI analysis revealed a positive ASMR correlation up to SDI 0.46, followed by an inverse relationship (<xref ref-type="fig" rid="fig4">Figure 4A</xref>). Countries with SDI&#x202F;&#x003E;&#x202F;0.5 demonstrated negative EAPC correlations in 2021 (<xref ref-type="fig" rid="fig4">Figure 4B</xref>). Similar changes were observed between ASDR and SDI (<xref ref-type="fig" rid="fig5">Figure 5</xref>).</p>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>IHD in GBD areas in 2021. <bold>(A)</bold> Relationship between ASMR and SDI, <bold>(B)</bold> Relationship between Super GBD areas in ASMR and SDI in 2021.</p>
</caption>
<graphic xlink:href="fnut-12-1658775-g004.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Two graphs illustrate the relationship between ASDR (Age-Standardized Death Rate) and the socio-demographic index. Graph A shows ASDR trends for different global regions, with colored lines representing each location. Graph B plots EAPC (Estimated Annual Percentage Change) of ASDR against the index for various countries, marked with dots varying in size representing DALYs (Disability-Adjusted Life Years) in 2021. The charts include legends for location, GBD region, and DALY size.</alt-text>
</graphic>
</fig>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>IHD in the 2021 GBD region. <bold>(A)</bold> Relationship between ASDR and SDI, <bold>(B)</bold> EAPC in the 2021 ASDR and SDI in the 2021 Super GBD region.</p>
</caption>
<graphic xlink:href="fnut-12-1658775-g005.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Two data visualizations depict ASMR and socio-demographic indices. Panel A shows ASMR per 100,000 across various global regions with distinct colored lines. Panel B illustrates EAPC of ASMR versus socio-demographic index in 2021, with dots representing countries' data points. The chart includes legends for location, the number of deaths in 2021, and GBD region classifications.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec sec-type="discussion" id="sec17">
<label>4</label>
<title>Discussion</title>
<p>From 1990 to 2021, the global IHD burden attributable to low seafood omega-3 intake showed falling ASMR/ASDR despite rising absolute deaths/DALYs; men and older adults consistently bore higher burdens; a strong SDI gradient was evident, with the steepest declines in high-SDI settings and limited progress in low-SDI regions; marked country heterogeneity included extremely low rates in high-income Asia-Pacific and unfavorable trends in selected small island states.</p>
<p>Omega-3 fatty acids, particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), exert cardiovascular protective effects through multiple molecular mechanisms. These include anti-inflammatory actions (e.g., suppression of pro-inflammatory factors), reduction of triglyceride synthesis, stabilization of atherosclerotic plaques, improvement of endothelial function, and anti-arrhythmic properties (<xref ref-type="bibr" rid="ref24">24</xref>, <xref ref-type="bibr" rid="ref30">30</xref>). Population studies support fish consumption as a preventive measure against coronary artery disease, chronic inflammation, and metabolic syndrome (<xref ref-type="bibr" rid="ref31">31</xref>). Epidemiological studies have demonstrated an inverse association between dietary fish consumption and coronary heart disease mortality, with optimal benefits (40&#x2013;60% risk reduction) observed at daily fish intake of 40-60&#x202F;g (<xref ref-type="bibr" rid="ref32">32</xref>). Omega-3 fatty acid supplementation reduces the risk of various cardiovascular conditions, including coronary artery disease, stroke, cardiac arrhythmias, and cardiovascular mortality (<xref ref-type="bibr" rid="ref30">30</xref>, <xref ref-type="bibr" rid="ref33">33</xref>, <xref ref-type="bibr" rid="ref34">34</xref>). Despite advances in conventional therapies such as statins and antiplatelet agents in reducing cardiovascular morbidity and mortality, additional preventive strategies remain necessary. Two large cardiovascular outcome trials of omega-3 fatty acids reached conflicting conclusions. REDUCE-IT (icosapent ethyl; pure EPA; mineral oil comparator) reported significant reductions in major adverse cardiovascular events, whereas STRENGTH (EPA&#x202F;+&#x202F;DHA carboxylic acids; corn oil comparator) was neutral and terminated for futility (<xref ref-type="bibr" rid="ref25">25</xref>, <xref ref-type="bibr" rid="ref26">26</xref>, <xref ref-type="bibr" rid="ref35">35</xref>, <xref ref-type="bibr" rid="ref36">36</xref>). Potential explanations include differences in formulation/active agent (pure EPA vs. EPA&#x202F;+&#x202F;DHA), comparators and their effects on lipids and inflammatory markers, achieved EPA exposure, baseline risk, adherence, and event rates. Elevated serum omega-3 levels correlate with reduced cardiovascular event risk, supporting their role in both primary and secondary prevention strategies for high-risk populations (<xref ref-type="bibr" rid="ref37 ref38 ref39">37&#x2013;39</xref>). While some studies demonstrate associations between dietary omega-3 fatty acids and chronic disease outcomes in free-living populations (<xref ref-type="bibr" rid="ref40">40</xref>, <xref ref-type="bibr" rid="ref41">41</xref>), others report no significant correlations (<xref ref-type="bibr" rid="ref42">42</xref>, <xref ref-type="bibr" rid="ref43">43</xref>). These mechanisms collectively explain the outcomes observed in randomized trials, such as the reduction in ischemic events with high-dose EPA in REDUCE-IT. Thus, the benefits of omega-3 intake stem from both biological mechanisms and population-level outcome measures, like decreased cardiovascular mortality. These inconsistent findings may be attributed to geographic dietary variations, methodological limitations in dietary assessment, or differences in fatty acid bioavailability.</p>
<p>Two large cardiovascular outcome trials of omega-3 fatty acids reached conflicting conclusions. REDUCE-IT (icosapent ethyl; pure EPA; mineral oil comparator) reported significant reductions in major adverse cardiovascular events, whereas STRENGTH (EPA&#x202F;+&#x202F;DHA carboxylic acids; corn oil comparator) was neutral and terminated for futility (<xref ref-type="bibr" rid="ref36">36</xref>). Potential explanations include differences in formulation/active agent (pure EPA vs. EPA&#x202F;+&#x202F;DHA), comparators and their effects on lipids and inflammatory markers, achieved EPA exposure, baseline risk, adherence, and event rates. From a dietary perspective, because seafood typically contains both EPA and DHA, STRENGTH may be compositionally more akin to habitual intake; however, pharmaceutical doses and exposures are far higher than those achieved with diet. Accordingly, these trials provide context and biological plausibility, but they should not be conflated with our GBD-based estimates of population-level burden attributable to low seafood omega-3 intake.</p>
<p>Studies show that men consistently have higher IHD mortality and DALY burdens than women. Men typically have higher exposure rates to cardiovascular risk factors, including obesity, smoking, and hypertension, which significantly increase the incidence and mortality of IHD (<xref ref-type="bibr" rid="ref4">4</xref>, <xref ref-type="bibr" rid="ref20">20</xref>). Additionally, hormonal changes in postmenopausal women, particularly the decline in estrogen levels, also significantly increase the risk of cardiovascular diseases (<xref ref-type="bibr" rid="ref44">44</xref>). Estrogen typically has cardioprotective effects by improving endothelial function, regulating lipid levels, and reducing inflammation, thereby lowering cardiovascular risk (<xref ref-type="bibr" rid="ref45">45</xref>). The reduction of estrogen after menopause may lead to the loss of these protective effects, thereby increasing the risk of IHD in older women (<xref ref-type="bibr" rid="ref46">46</xref>).</p>
<p>Age plays a key role. Research shows that IHD mortality and DALYs burdens peak in individuals aged 75&#x2013;79, likely due to the accumulated effects of atherosclerosis, cardiovascular degeneration, and other chronic conditions in older adults (<xref ref-type="bibr" rid="ref21">21</xref>). Cardiac structural and functional changes in older adults, including myocardial fibrosis, coronary sclerosis, and decreased vascular compliance, further elevate IHD risk (<xref ref-type="bibr" rid="ref47">47</xref>). Moreover, older adults frequently present with comorbidities such as diabetes, chronic kidney disease, and hypertension, which commonly overlap with cardiovascular diseases, intensifying the overall IHD burden (<xref ref-type="bibr" rid="ref48 ref49 ref50 ref51">48&#x2013;51</xref>).</p>
<p>Men and older adults may be more sensitive to insufficient omega-3 fatty acid intake (<xref ref-type="bibr" rid="ref52">52</xref>). Omega-3 fatty acids, particularly EPA and DHA, possess anti-inflammatory, lipid-lowering properties, enhance endothelial function, and stabilize atherosclerotic plaques (<xref ref-type="bibr" rid="ref12">12</xref>, <xref ref-type="bibr" rid="ref53">53</xref>). Elevated chronic systemic inflammation in men and older adults may impair the body&#x2019;s capacity to repair cardiovascular damage, thereby increasing reliance on the protective benefits of omega-3 fatty acids (<xref ref-type="bibr" rid="ref49">49</xref>, <xref ref-type="bibr" rid="ref54">54</xref>). Omega-3 deficiency may further exacerbate inflammatory responses, leading to an increased risk of IHD (<xref ref-type="bibr" rid="ref53">53</xref>, <xref ref-type="bibr" rid="ref55">55</xref>).</p>
<p>Our findings align with evidence that marine omega-3&#x202F;s (EPA/DHA) exert triglyceride-lowering, anti-inflammatory, plaque-stabilizing and antiarrhythmic effects, supporting targeted supplementation strategies. In high-risk patients with residual risk on statins, purified EPA lowered ischemic event burden (REDUCE-IT), whereas population-wide guidance emphasizes regular fish consumption as a pragmatic foundation. Translating these insights to low- and middle-SDI settings requires context-specific access, affordability, and food-system policies (<xref ref-type="bibr" rid="ref12">12</xref>, <xref ref-type="bibr" rid="ref15">15</xref>, <xref ref-type="bibr" rid="ref24 ref25 ref26">24&#x2013;26</xref>).</p>
<p>Singapore (high-income Asia-Pacific) exhibited very low omega-3-attributable IHD rates, plausibly reflecting high SDI, strong CVD prevention programs, and comparatively high seafood access. In contrast, Nauru (small island state) showed increasing trends, consistent with its heavy cardiometabolic risk burden and small-population rate instability (wide UIs). The Maldives combines very high per-capita fish intake with small-population data constraints, yielding extreme values with broader uncertainty. GBD explicitly addresses sparse vital registration via covariates, garbage-code redistribution, and DisMod-MR synthesis; nevertheless, residual bias from diagnostic capacity, coding practice, and survey representativeness may persist, and we now acknowledge these uncertainties in the limitations.</p>
<p>Moreover, socioeconomic factors and lifestyle differences may further explain these gender- and age-related disparities. Additionally, socioeconomic factors and lifestyle differences may further exacerbate the disparities. In high-SDI regions, the burden of IHD has decreased significantly (EAPC for ASMR and ASDR are &#x2212;4.01 and &#x2212;3.59, respectively), while improvements in low-SDI regions are smaller, and some areas (e.g., parts of sub-Saharan Africa) show negative trends or remain stable. In high-SDI regions, healthcare systems and technologies are more advanced, enabling early diagnosis, treatment, and management of cardiovascular diseases. Statin medications can reduce cholesterol levels, and antiplatelet therapy can prevent thrombosis. These measures have reduced the incidence and mortality of ischemic heart disease (IHD) (<xref ref-type="bibr" rid="ref56">56</xref>). In low-SDI regions, inadequate medical facilities and resources hinder the timely diagnosis and treatment of IHD (<xref ref-type="bibr" rid="ref50">50</xref>). Economic development has increased per capita income, improving dietary quality (<xref ref-type="bibr" rid="ref57">57</xref>). More people can afford to eat deep-sea fish rich in Omega-3 fatty acids, such as salmon, mackerel, and tuna, thereby reducing health risks associated with Omega-3 deficiency (<xref ref-type="bibr" rid="ref14">14</xref>). People in low-SDI regions often lack sufficient Omega-3 fatty acid intake due to monotonous diets centered around grains and economic constraints limiting access to seafood (<xref ref-type="bibr" rid="ref52">52</xref>). The COVID-19 pandemic disrupted food supply chains, further limiting access to nutrient-rich foods in these regions and exacerbating nutritional deficiencies (<xref ref-type="bibr" rid="ref58">58</xref>, <xref ref-type="bibr" rid="ref59">59</xref>).</p>
<p>Projected demographic shifts indicate that by 2050, individuals aged over 60 will comprise more than 20% of the global population (<xref ref-type="bibr" rid="ref60">60</xref>), a trend that will further increase the burden of IHD in older populations. Increasing omega-3 fatty acid intake should be prioritized as a core preventive measure, particularly among high-risk groups. Furthermore, comprehensive interventions (including smoking cessation, limiting alcohol consumption, promoting fish intake, reducing sodium intake, increasing physical activity, and improving cardiovascular care in resource-limited settings) can significantly reduce the incidence and mortality of cardiovascular diseases. Finally, further research is needed to delve into the specific mechanisms underlying gender and age differences.</p>
<p>This study confirms the critical role of omega-3 fatty acid deficiency in contributing to the burden of CVD, aligning with findings from existing literature (<xref ref-type="bibr" rid="ref61">61</xref>). For example, Mozaffarian and Wu (<xref ref-type="bibr" rid="ref19">19</xref>) highlighted that Omega-3 fatty acids reduce cardiovascular disease risk by lowering blood lipids, reducing inflammation, and stabilizing atherosclerotic plaques. This study found that the decline in IHD burden in high-SDI regions aligns with Yusuf et al. (<xref ref-type="bibr" rid="ref56">56</xref>), who emphasized that improving healthcare infrastructure and promoting healthy diets effectively reduce cardiovascular disease burdens. Additionally, our research showed that the increasing IHD burden in low-SDI regions (e.g., sub-Saharan Africa) is associated with inadequate omega-3 fatty acid intake, consistent with Micha et al. (<xref ref-type="bibr" rid="ref52">52</xref>), who reported dietary deficiencies in low-income countries. This study also found that men and older adults experience a higher IHD burden, supporting Virani et al. (<xref ref-type="bibr" rid="ref20">20</xref>). They explained that men face higher IHD risks due to greater exposure to factors like smoking and hypertension, while older adults are more affected because of advanced atherosclerosis. This study specifically focuses on the effects of insufficient omega-3 fatty acid intake, whereas other dietary risk-related studies have examined the impact of high sugar, high salt, or low-fiber diets (<xref ref-type="bibr" rid="ref62">62</xref>). By emphasizing omega-3 deficiency, this study fills a significant research gap in the global understanding of this dietary risk factor. Compared to commonly studied dietary risks in GBD 2019 literature, research on omega-3 fatty acid deficiency is more novel and holds greater academic significance (<xref ref-type="bibr" rid="ref63 ref64 ref65 ref66">63&#x2013;66</xref>).</p>
<p>Marine omega-3 long-chain polyunsaturated fatty acids may influence several intermediate cardiovascular risk factors. First, EPA/DHA lower triglycerides primarily by reducing hepatic VLDL production and enhancing clearance, yielding clinically meaningful reductions (<xref ref-type="bibr" rid="ref67">67</xref>, <xref ref-type="bibr" rid="ref68">68</xref>). Second, small decreases in blood pressure and improvements in endothelial and inflammatory profiles have been reported (<xref ref-type="bibr" rid="ref69">69</xref>). Third, omega-3&#x202F;s exert a modest negative chronotropic effect, lowering resting heart rate&#x2014;an emerging cardiovascular risk factor. Meta-analyses demonstrate that omega-3 supplementation reduces resting heart rate by approximately 1.6 beats per minute (bpm), with dose-dependent effects observed at intakes &#x2265;1&#x202F;g/day (<xref ref-type="bibr" rid="ref70">70</xref>). This heart rate reduction is clinically meaningful, as epidemiological evidence shows that each 1-bpm increase in resting heart rate is associated with a 2% increase in all-cause mortality and a 1% increase in cardiovascular mortality (<xref ref-type="bibr" rid="ref71">71</xref>, <xref ref-type="bibr" rid="ref72">72</xref>). The heart rate-lowering effect of omega-3 fatty acids may contribute to their antiarrhythmic protection and overall cardiovascular benefit. These mechanisms are consistent with&#x2014;but not equivalent to&#x2014;clinical endpoint reductions and provide biological plausibility for the attributable burden estimated in our study.</p>
<p>This study provides a valuable contribution to understanding the global burden of IHD associated with omega-3 fatty acid deficiency. Using data from the GBD 2021 database, we analyzed the impact of dietary risk factors on the global burden of IHD. The GBD 2021 database spans data from 1990 to 2021 and includes updated results for the most recent 2&#x202F;years, particularly addressing the disease burden caused by the COVID-19 pandemic in 2020 and 2021, along with adjustments to the burden of other diseases. Importantly, GBD 2021 incorporates model optimizations based on GBD 2019. Spanning the years 1990 to 2021, this study illustrates the long-term trends in the IHD burden related to omega-3 deficiency, particularly quantifying regional burden changes using the EAPC metric. While previous research on the global impact of omega-3 fatty acids on IHD has been limited, this study comprehensively quantifies the disease burden of omega-3 deficiency using GBD data, along with an exploration of mechanisms and regional differences, thereby addressing this critical gap.</p>
</sec>
<sec id="sec18">
<label>5</label>
<title>Limitations</title>
<p>There were some limitations of this study that were worth noting. This study utilizes data from the GBD database, which does not differentiate between the specific effects of DHA and EPA, making it impossible to assess their distinct impacts on the IHD burden. The GBD database integrates data from diverse sources, including national health surveys, scientific publications, and statistical models. However, data quality and completeness vary significantly across countries, with low- and middle-income regions often experiencing data gaps or inaccuracies due to underdeveloped health surveillance systems, potentially biasing global IHD estimates.</p>
<p>Although this study spans 32&#x202F;years and covers 204 countries, it does not account for detailed temporal changes in dietary patterns, fish consumption, or seafood availability. The assumption of regional homogeneity may also obscure significant subnational variations in omega-3 intake and IHD burden. As an observational study based on secondary data, causality between omega-3 deficiency and IHD burden cannot be established. While statistical associations are observed, experimental studies or randomized controlled trials (RCTs) are required to validate these findings and quantify the direct effects of omega-3 intake on IHD risk reduction.</p>
<p>Across regions, viability of IHD diagnostic criteria varies with access to ECG/troponin testing, catheterization, and clinician coding practices. Transitions from ICD-9 to ICD-10, incomplete vital registration, and differential adoption of high-sensitivity biomarkers may introduce ascertainment biases. Although GBD harmonizes definitions and applies garbage-code redistribution and cross-walks, residual heterogeneity likely remains, particularly in low-resource settings; hence, our country-level estimates should be interpreted alongside UIs and health-system context (<xref ref-type="bibr" rid="ref2">2</xref>, <xref ref-type="bibr" rid="ref3">3</xref>, <xref ref-type="bibr" rid="ref28">28</xref>).</p>
<p>The estimation of ASMR and ASDR depends on assumptions within the GBD statistical models, such as using SDI as a proxy for development. These assumptions may fail to fully capture the intricate relationships between dietary practices, socioeconomic conditions, and healthcare systems, potentially limiting the precision of the results. This study specifically examines the association between omega-3 deficiency and IHD burden using GBD data, while other aspects, such as environmental influences on omega-3 levels or its role in specific subpopulations, fall outside the scope of this analysis.</p>
<p>As an ecological analysis, this study cannot establish causality between omega-3 deficiency and IHD outcomes. The observed associations are susceptible to confounding by unmeasured dietary factors (protein intake, micronutrients, overall dietary quality) and socioeconomic determinants beyond SDI (healthcare access, lifestyle behaviors, environmental exposures). Populations with adequate omega-3 intake typically exhibit better overall nutritional status and healthcare infrastructure. Consequently, the GBD burden estimates likely overestimate the true causal effect of omega-3 deficiency and should be interpreted as hypothesis-generating associations rather than evidence supporting single-nutrient interventions.</p>
</sec>
<sec sec-type="conclusions" id="sec19">
<label>6</label>
<title>Conclusion</title>
<p>From 1990 to 2021, the IHD burden attributable to low seafood omega-3 intake declined in age-standardized terms but rose in absolute numbers, with men, older adults, and low- to middle-SDI regions most affected. These findings reinforce omega-3 intake as a modifiable factor and highlight the need for context-appropriate policies that expand access to fish or effective supplementation, particularly in resource-limited settings. Strengthening diagnostic capacity and data systems will improve comparability and targeting of prevention.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec20">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">Supplementary material</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec sec-type="ethics-statement" id="sec21">
<title>Ethics statement</title>
<p>Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the patients was not required to participate in this study in accordance with the national legislation and the institutional requirements.</p>
</sec>
<sec sec-type="author-contributions" id="sec22">
<title>Author contributions</title>
<p>XC: Conceptualization, Methodology, Resources, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. LC: Conceptualization, Data curation, Methodology, Project administration, Resources, Supervision, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. XY: Data curation, Formal analysis, Methodology, Project administration, Supervision, Validation, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. ZZ: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec sec-type="COI-statement" id="sec24">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="sec25">
<title>Generative AI statement</title>
<p>The authors declare that Gen AI was used in the creation of this manuscript. During the preparation of this work the authors used Poe in order to polish the language. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.</p>
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<sec sec-type="disclaimer" id="sec26">
<title>Publisher&#x2019;s note</title>
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</sec>
<sec sec-type="supplementary-material" id="sec27">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fnut.2025.1658775/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fnut.2025.1658775/full#supplementary-material</ext-link></p>
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<fn-group>
<fn id="fn0002" fn-type="custom" custom-type="edited-by"><p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3140970/overview">Annalisa Giosu&#x00E8;</ext-link>, University of Naples Federico II, Italy</p></fn>
<fn id="fn0003" fn-type="custom" custom-type="reviewed-by"><p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/967389/overview">Rizaldy Taslim Pinzon</ext-link>, Duta Wacana Christian University, Indonesia</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/281519/overview">Weiguo Zhang</ext-link>, Las Colinas Institutes, United States</p></fn>
</fn-group>
<fn-group>
<fn id="fn0001"><p><sup>1</sup><ext-link xlink:href="http://ghdx.healthdata.org/gbd-results-tool" ext-link-type="uri">http://ghdx.healthdata.org/gbd-results-tool</ext-link></p></fn>
</fn-group></back>
</article>