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<journal-id journal-id-type="publisher-id">Front. Public Health</journal-id>
<journal-title>Frontiers in Public Health</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Public Health</abbrev-journal-title>
<issn pub-type="epub">2296-2565</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fpubh.2025.1605624</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Public Health</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Comparative global burden of ischemic heart disease and myocardial disease attributable to non-optimal temperatures, 1990&#x02013;2021: an analysis based on GBD 2021</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name><surname>Guo</surname> <given-names>Mengqi</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
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<contrib contrib-type="author">
<name><surname>Lian</surname> <given-names>Zhexun</given-names></name>
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</contrib>
<contrib contrib-type="author">
<name><surname>Xia</surname> <given-names>Zongyi</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Lingbing</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name><surname>Xin</surname> <given-names>Hui</given-names></name>
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<contrib contrib-type="author" corresp="yes">
<name><surname>Li</surname> <given-names>Fuhai</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
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<aff id="aff1"><sup>1</sup><institution>Department of Cardiology, The Affiliated Hospital of Qingdao University</institution>, <addr-line>Qingdao, Shandong</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Clinical Medicine, Shandong Second Medical University</institution>, <addr-line>Weifang, Shandong</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>Department of Cardiology, Third People&#x00027;s Hospital of Huizhou, Guangzhou Medical University</institution>, <addr-line>Huizhou, Guangdong</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Arthit Phosri, Mahidol University, Thailand</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Nishant Raj Kapoor, Academy of Scientific and Innovative Research (AcSIR), India</p>
<p>Quankai Cheng, Second Affiliated Hospital of Xi&#x00027;an Jiaotong University, China</p></fn>
<corresp id="c001">&#x0002A;Correspondence: Mengqi Guo <email>guomq628&#x00040;qdu.edu.cn</email></corresp>
<corresp id="c003">Fuhai Li <email>fhli&#x00040;qdu.edu.cn</email></corresp>
<corresp id="c002">Hui Xin <email>xinhuiqy&#x00040;163.com</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>23</day>
<month>09</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>13</volume>
<elocation-id>1605624</elocation-id>
<history>
<date date-type="received">
<day>03</day>
<month>04</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>28</day>
<month>07</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2025 Guo, Lian, Xia, Wang, Xin and Li.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Guo, Lian, Xia, Wang, Xin and Li</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license>
</permissions>
<abstract>
<sec>
<title>Objectives</title>
<p>To compare the global burden of myocardial disease (MD) and ischemic heart disease (IHD) attributable to high and low temperatures, and to examine demographic and socio-economic disparities over time.</p>
</sec>
<sec>
<title>Methods</title>
<p>We analyzed disability-adjusted life years (DALYs) and mortality for MD and IHD attributable to high and low temperatures, stratified by sex, age, region, and socio-demographic index (SDI). Decomposition analysis quantified the contributions of population growth, aging, and epidemiological changes. Projections were generated using an age-period-cohort model.</p>
</sec>
<sec>
<title>Results</title>
<p>Between 1990 and 2021, high temperature-related MD and IHD burdens increased [Estimated Annual Percent Change (EAPC): &#x0002B;1.26 and &#x0002B;1.68%, respectively], whereas low temperature burdens declined (EAPC: &#x02212;1.87 and &#x02212;1.73%) but remained considerably higher overall. MD disproportionately affected children under five and adults over 80, while IHD rarely appeared under 30 yet rose markedly from midlife onward. Heat-related MD and IHD burdens rose with SDI &#x0003C; 0.5 and declined above 0.5; cold-related burdens decreased consistently above SDI 0.75 but varied irregularly below this threshold. Central Asia exhibited the greatest heat- and cold-related burdens for both MD and IHD, whereas North Africa and the Middle East were particularly susceptible to heat. Population growth primarily fueled heat-related burdens, whereas cold-related burdens were more driven by aging and population change. Projections to 2040 indicate continuing increases in heat-related burdens, potentially exacerbating health disparities.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>Heat-attributable IHD is the fastest-growing threat, while MD remains critical for very young and older adult populations under extreme temperatures. Disparities across age, SDI, and geography highlight the urgency for targeted interventions.</p>
</sec></abstract>
<kwd-group>
<kwd>myocardial disease</kwd>
<kwd>ischemic heart disease</kwd>
<kwd>extreme temperatures</kwd>
<kwd>GBD</kwd>
<kwd>DALYs</kwd>
<kwd>mortality</kwd>
</kwd-group>
<counts>
<fig-count count="6"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="57"/>
<page-count count="19"/>
<word-count count="11292"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Environmental Health and Exposome</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>Cardiovascular disease (CVD) remains the leading cause of death worldwide. In 2021, there were an estimated 612 million people living with CVD, accounting for 26.8% of all global deaths (<xref ref-type="bibr" rid="B1">1</xref>). Ischemic heart disease (IHD) has consistently been the top cause of age-standardized mortality, responsible for over 9 million deaths in 2019&#x02014;nearly 16% of global mortality&#x02014;and contributing significantly to disability-adjusted life years (DALYs) (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B3">3</xref>). IHD primarily results from atherosclerosis or coronary spasms, restricting coronary blood flow and leading to myocardial infarction or chronic coronary syndromes.</p>
<p>Myocardial disease (MD), including cardiomyopathy and myocarditis, affects cardiac structure and function through mechanisms such as genetic mutations, infections, and autoimmune processes. In 2019, inflammatory cardiomyopathy and myocarditis caused &#x0007E;340,349 deaths globally, with an age-standardized mortality rate of 4.40 per 100,000, affecting mainly older adults and men (<xref ref-type="bibr" rid="B4">4</xref>). While MD is less prevalent than IHD, it can cause severe morbidity and disproportionately impacts younger individuals, including children and young adults, particularly in less developed regions (<xref ref-type="bibr" rid="B5">5</xref>).</p>
<p>Environmental factors, particularly climate change, are increasingly implicated in the global CVD burden (<xref ref-type="bibr" rid="B6">6</xref>). Children born today may face lifetime temperatures 4&#x000B0;C above pre-industrial levels (<xref ref-type="bibr" rid="B7">7</xref>). Global temperatures over the past 7 years have been the highest on record, and each day of heat exposure increases monthly cardiovascular mortality by 0.12% among adults aged 20 and older (<xref ref-type="bibr" rid="B8">8</xref>). Simultaneously, Arctic ice melt and altered atmospheric patterns contribute to more frequent cold extremes, elevating CVD mortality in affected regions (<xref ref-type="bibr" rid="B9">9</xref>).</p>
<p>Both extreme high and low temperatures pose distinct risks for CVD patients. Heat exposure exacerbates dehydration, electrolyte imbalances, and increased blood viscosity, triggering arrhythmias, heart failure, or acute coronary events (<xref ref-type="bibr" rid="B10">10</xref>). In contrast, cold exposure raises blood pressure and systemic inflammation, straining cardiac function and increasing risks of myocardial infarction or heart failure (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>). Despite known associations, existing studies often focus on aggregate cardiovascular outcomes rather than disease-specific impacts, leaving geographic and socioeconomic differences underexplored (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>). Our study fills these gaps by quantifying the global burdens attributable to non-optimal temperatures for IHD and MD separately and by providing detailed demographic and regional breakdowns to guide targeted interventions.</p>
</sec>
<sec sec-type="methods" id="s2">
<title>Methods</title>
<sec>
<title>Data sources</title>
<p>The Global Burden of Diseases (GBD) 2021 study, conducted by the Institute for Health Metrics and Evaluation (IHME), provides comprehensive estimates for 369 diseases and 88 risk factors across 204 countries or regions. Study design and methods are detailed in prior GBD literature (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B15">15</xref>). The University of Washington IRB waived informed consent for GBD data access (<xref ref-type="bibr" rid="B16">16</xref>). This study adhered to the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) (<xref ref-type="bibr" rid="B17">17</xref>).</p>
</sec>
<sec>
<title>Defining non-optimal temperatures</title>
<p>Temperature estimates were derived from the ERA5 reanalysis dataset, provided by the European Center for Medium-Range Weather Forecasts, which offers high-resolution (0.25&#x000B0; &#x000D7; 0.25&#x000B0;) temperature data from 1979 to the present. Non-optimal temperatures were defined as temperatures exceeding or falling below the theoretical minimum risk exposure level, which corresponds to daily temperatures associated with the lowest mortality rates for specific locations. To mitigate the influence of extreme temperatures and noise, data were truncated, preventing extrapolation of temperatures beyond the range of mortality data. Temperature ranges were truncated at the 1st and 99th percentiles of the mortality dataset, and daily mean temperatures were similarly truncated within each temperature range (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B18">18</xref>).</p>
</sec>
<sec>
<title>Estimated cardiovascular disease burden attributable to non-optimal temperature exposures</title>
<p>Non-optimal temperatures, including both extreme high and low temperatures, are identified as risk factors for myocarditis/cardiomyopathy (referred to as myocardial disease; MD) and ischemic heart disease (IHD) in the GBD database. Cause-specific relative risks of non-optimal temperature on daily mortality in the Global Burden of Disease Study were estimated using methods by Burkart et al. (<xref ref-type="bibr" rid="B19">19</xref>). Firstly, a Bayesian meta-regression framework with a two-dimensional spline model was applied to analyze the relative risks of 176 causes of death related to daily temperature. These relative risks were then applied globally, using daily temperature data combined with Global Burden of Disease Study data to calculate disease burden for each region.</p>
</sec>
<sec>
<title>Data analysis</title>
<p>Burden was measured using mortality and disability-adjusted life years (DALYs), comprising years of life lost and years lived with disability (YLD). Age-standardized rates were calculated using the direct method with the GBD 2019 standard population as a reference, expressed per 100,000 population (ASMR for mortality, ASDR for DALYs). Age standardization was applied to eliminate the confounding effects of different population age structures across regions. Trends from 1990 to 2021 were assessed using Estimated Annual Percent Change (EAPC); Total Percentage Change (TPC) was used for regions with missing or negative values. Analyses were stratified by sex, 5-year age groups, and socio-demographic index (SDI) categories to capture burden patterns at global, regional, and national levels.</p>
<sec>
<title>Decomposition analysis</title>
<p>To understand the contributions of population growth, aging, and epidemiological shifts, we conducted a decomposition analysis. This method involved comparing the observed burden in 2021 with hypothetical scenarios that isolated each of these three factors separately. Specifically, we recalculated DALYs and mortality assuming: (1) population size and age structure remained constant while disease rates changed (epidemiological changes), (2) age-specific rates and total population size were constant while age structure changed (aging effects), and (3) age-specific rates and age structure remained constant while the population size changed (population growth effects). The relative contributions of each factor were then quantified by comparing these hypothetical scenarios to the observed 2021 data (<xref ref-type="bibr" rid="B20">20</xref>).</p>
</sec>
<sec>
<title>Predicting trends</title>
<p>Future cases and incidence rates (2021&#x02013;2040) were projected using a log-linear age-period-cohort model (<xref ref-type="bibr" rid="B21">21</xref>). Specifically, we utilized the NORDPRED package in R, applying age-period-cohort modeling to historical age-specific rates to estimate future incidence and mortality rates. Trends were projected by logarithmically extrapolating observed changes, with adjustments assuming gradually decreasing trends in increments of 25%, 50%, and 75% reductions applied sequentially across forecast intervals. Projections for the final year (2040) combined weighted averages of the preceding two forecast intervals, adjusted using United Nations national population forecasts for consistency (<xref ref-type="bibr" rid="B22">22</xref>). Analyses were conducted in R Studio using the NORDPRED package, with statistical significance set at <italic>P</italic> &#x0003C; 0.05.</p>
</sec>
</sec>
<sec>
<title>Statistical analysis</title>
<p>A positive 95% confidence interval indicated increasing trends, negative values indicated decreases, and intervals including zero suggested stability. All analyses were performed using R (version 4.2.1), with a two-sided <italic>P</italic>-value &#x0003C; 0.05 considered significant.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec>
<title>Global assessment of cardiovascular burden from extreme temperatures (1990&#x02013;2021)</title>
<p>From 1990 to 2021, age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) attributable to high temperatures for myocardial disease (MD) and ischemic heart disease (IHD) generally increased, although with fluctuations. By 2021, the ASDR for heat-attributable MD was 1.97 per 100,000 (95% CI: &#x02212;0.80 to 4.76), corresponding to 158,029 DALYs, while the ASMR reached 0.06 per 100,000 (95% CI: &#x02212;0.02 to 0.15), with 5,224 deaths. For IHD, the ASDR was 30.57 per 100,000 (95% CI: 5.41 to 66.96), amounting to 2,623,940 DALYs, with an ASMR of 1.34 per 100,000 (95% CI: 0.20&#x02013;3.07), corresponding to 112,390 deaths. Over 30 years, the estimated annual percent change (EAPC) in DALYs attributable to high temperatures was 1.26% (95% CI: 0.78% &#x02212;1.75%) for MD, and 1.68% (95% CI: 1.33% &#x02212;2.03%) for IHD. Mortality rates showed similar trends, with EAPCs of 1.35% (95% CI: 0.86% &#x02212;1.85%) and 1.66% (95% CI: 1.31% &#x02212;2%), respectively (<xref ref-type="fig" rid="F1">Figure 1</xref>).</p>
<fig position="float" id="F1">
<label>Figure 1</label>
<caption><p>Age-standardized DALYs rate (ASDR) for myocardial disease, and ischemic heart disease attributable to high and low temperatures from 1990 to 2021, stratified by the sociodemographic index (SDI). DALYs, Disability-adjusted life years.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpubh-13-1605624-g0001.tif">
<alt-text>Six line graphs show age-standardized Disability-Adjusted Life Year (DALY) rates for myocardial and ischemic heart diseases. Rates are categorized by sex (both, female, male) and Socio-demographic Index (SDI) levels from 1990 to 2020. Lines represent global, high, high-middle, middle, low-middle, and low SDI, with notable variations across SDI levels and diseases.</alt-text>
</graphic>
</fig>
<p>In contrast, ASMR and ASDR attributable to low temperatures, although historically higher, showed consistent reductions over time. By 2021, the ASDR for cold-attributable MD was 7.01 per 100,000 (95% CI: 5.35&#x02013;9.03), corresponding to 578,936 DALYs, with an ASMR of 0.27 per 100,000 (95% CI: 0.21&#x02013;0.34), reflecting 22,248 deaths. For IHD, the ASDR was 117.40 per 100,000 (95% CI: 101.19&#x02013;144.86), accounting for 9,961,231 DALYs, and the ASMR was 6.14 per 100,000 (95% CI: 5.23&#x02013;7.53), corresponding to 505,298 deaths. The EAPC in DALYs attributable to low temperatures was &#x02212;1.87% (&#x02212;2.17% &#x02212;1.58%) for MD, and &#x02212;1.73% (95% CI: &#x02212;1.85% &#x02212;1.6%) for IHD, with similar decreasing trends observed in ASMR (<xref ref-type="fig" rid="F1">Figure 1</xref> and <xref ref-type="table" rid="T1">Table 1</xref>).</p>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p>Global and SDI-region-specific DALYs and mortality rates (ASDR, ASMR), with EAPC values for myocardial disease, and ischemic heart disease attributable to high and low temperatures in 1990 vs. 2021.</p></caption>
<table frame="box" rules="all">
<thead>
<tr>
<th rowspan="2" valign="top" align="left"><bold>Location</bold></th>
<th valign="top" align="center" colspan="4"><bold>Total ASDR (95% UI)</bold></th>
<th valign="top" align="center" colspan="4"><bold>Female ASDR (95% UI)</bold></th>
<th valign="top" align="center" colspan="4"><bold>Male ASDR (95% UI)</bold></th>
</tr>
<tr>
<th valign="top" align="center"><bold>1990</bold></th>
<th valign="top" align="center"><bold>2021</bold></th>
<th valign="top" align="center"><bold>TPC</bold></th>
<th valign="top" align="center"><bold>EAPC</bold></th>
<th valign="top" align="center"><bold>1990</bold></th>
<th valign="top" align="center"><bold>2021</bold></th>
<th valign="top" align="center"><bold>TPC</bold></th>
<th valign="top" align="center"><bold>EAPC</bold></th>
<th valign="top" align="center"><bold>1990</bold></th>
<th valign="top" align="center"><bold>2021</bold></th>
<th valign="top" align="center"><bold>TPC</bold></th>
<th valign="top" align="center"><bold>EAPC</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" colspan="13"><bold>Myocardial disease attributable to high temperature (1990 vs. 2021)</bold></td>
</tr> <tr>
<td valign="top" align="left">Global</td>
<td valign="top" align="center">1.60 (&#x02212;0.75, 4.38)</td>
<td valign="top" align="center">1.97 (&#x02212;0.80, 4.76)</td>
<td valign="top" align="center">0.23 (&#x02212;0.30, 1.40)</td>
<td valign="top" align="center">1.26 (0.78&#x02013;1.75)</td>
<td valign="top" align="center">1.34 (&#x02212;0.50, 3.73)</td>
<td valign="top" align="center">1.43 (&#x02212;0.50, 3.35)</td>
<td valign="top" align="center">0.07 (&#x02212;0.64, 1.09)</td>
<td valign="top" align="center">0.93 (0.45&#x02013;1.41)</td>
<td valign="top" align="center">1.90 (&#x02212;0.93, 5.13)</td>
<td valign="top" align="center">2.54 (&#x02212;1.09, 6.31)</td>
<td valign="top" align="center">0.34 (&#x02212;0.25, 1.72)</td>
<td valign="top" align="center">1.47 (0.97&#x02013;1.97)</td>
</tr> <tr>
<td valign="top" align="left">High SDI</td>
<td valign="top" align="center">1.64 (&#x02212;0.33, 3.95)</td>
<td valign="top" align="center">1.27 (&#x02212;0.14, 2.74)</td>
<td valign="top" align="center">&#x02212;0.23 (&#x02212;0.78, 0.13)</td>
<td valign="top" align="center">&#x02212;0.29 (&#x02212;0.74&#x02013;0.16)</td>
<td valign="top" align="center">1.20 (&#x02212;0.24, 2.87)</td>
<td valign="top" align="center">0.81 (&#x02212;0.08, 1.77)</td>
<td valign="top" align="center">&#x02212;0.33 (&#x02212;0.82, &#x02212;0.05)</td>
<td valign="top" align="center">&#x02212;0.74 (&#x02212;1.21&#x02013;&#x02212;0.27)</td>
<td valign="top" align="center">2.16 (&#x02212;0.46, 5.19)</td>
<td valign="top" align="center">1.73 (&#x02212;0.19, 3.76)</td>
<td valign="top" align="center">&#x02212;0.20 (&#x02212;0.76, 0.15)</td>
<td valign="top" align="center">&#x02212;0.15 (&#x02212;0.61&#x02013;0.3)</td>
</tr> <tr>
<td valign="top" align="left">Middle-high SDI</td>
<td valign="top" align="center">0.89 (&#x02212;0.46, 2.61)</td>
<td valign="top" align="center">1.32 (&#x02212;0.94, 3.74)</td>
<td valign="top" align="center">0.49 (&#x02212;0.35, 1.46)</td>
<td valign="top" align="center">0.97 (0.21&#x02013;1.73)</td>
<td valign="top" align="center">0.71 (&#x02212;0.32, 2.03)</td>
<td valign="top" align="center">0.77 (&#x02212;0.48, 2.11)</td>
<td valign="top" align="center">0.09 (&#x02212;0.61, 0.84)</td>
<td valign="top" align="center">0.01 (&#x02212;0.66&#x02013;0.7)</td>
<td valign="top" align="center">1.10 (&#x02212;0.61, 3.29)</td>
<td valign="top" align="center">1.89 (&#x02212;1.39, 5.45)</td>
<td valign="top" align="center">0.73 (&#x02212;0.50, 1.85)</td>
<td valign="top" align="center">1.42 (0.62&#x02013;2.22)</td>
</tr> <tr>
<td valign="top" align="left">Middle SDI</td>
<td valign="top" align="center">1.53 (&#x02212;0.40, 3.45)</td>
<td valign="top" align="center">1.57 (&#x02212;0.31, 3.29)</td>
<td valign="top" align="center">0.03 (&#x02212;0.32, 0.57)</td>
<td valign="top" align="center">0.54 (0.12&#x02013;0.96)</td>
<td valign="top" align="center">1.38 (&#x02212;0.28, 3.09)</td>
<td valign="top" align="center">1.16 (&#x02212;0.20, 2.46)</td>
<td valign="top" align="center">&#x02212;0.16 (&#x02212;0.48, 0.45)</td>
<td valign="top" align="center">0.02 (&#x02212;0.41&#x02013;0.44)</td>
<td valign="top" align="center">1.68 (&#x02212;0.50, 3.92)</td>
<td valign="top" align="center">2.01 (&#x02212;0.42, 4.34)</td>
<td valign="top" align="center">0.19 (&#x02212;0.28, 1.13)</td>
<td valign="top" align="center">0.94 (0.52&#x02013;1.36)</td>
</tr> <tr>
<td valign="top" align="left">Middle-low SDI</td>
<td valign="top" align="center">2.61 (&#x02212;1.58, 7.50)</td>
<td valign="top" align="center">3.93 (&#x02212;1.32, 9.57)</td>
<td valign="top" align="center">0.51 (&#x02212;3.75, 4.51)</td>
<td valign="top" align="center">2 (1.37&#x02013;2.63)</td>
<td valign="top" align="center">2.18 (&#x02212;1.02, 6.87)</td>
<td valign="top" align="center">2.96 (&#x02212;0.81, 7.16)</td>
<td valign="top" align="center">0.36 (&#x02212;2.91, 8.00)</td>
<td valign="top" align="center">1.8 (1.18&#x02013;2.43)</td>
<td valign="top" align="center">3.03 (&#x02212;1.70, 9.08)</td>
<td valign="top" align="center">4.99 (&#x02212;1.81, 12.56)</td>
<td valign="top" align="center">0.65 (&#x02212;2.23, 4.90)</td>
<td valign="top" align="center">2.19 (1.56&#x02013;2.83)</td>
</tr> <tr>
<td valign="top" align="left">Low SDI</td>
<td valign="top" align="center">1.30 (&#x02212;2.48, 7.35)</td>
<td valign="top" align="center">2.38 (&#x02212;2.14, 7.88)</td>
<td valign="top" align="center">0.83 (&#x02212;9.06, 7.65)</td>
<td valign="top" align="center">2.8 (1.79&#x02013;3.81)</td>
<td valign="top" align="center">1.13 (&#x02212;2.18, 6.40)</td>
<td valign="top" align="center">1.80 (&#x02212;1.33, 5.87)</td>
<td valign="top" align="center">0.59 (&#x02212;8.43, 4.82)</td>
<td valign="top" align="center">2.35 (1.38&#x02013;3.32)</td>
<td valign="top" align="center">1.46 (&#x02212;3.06, 8.18)</td>
<td valign="top" align="center">2.99 (&#x02212;2.91, 10.33)</td>
<td valign="top" align="center">1.05 (&#x02212;5.92, 11.14)</td>
<td valign="top" align="center">3.14 (2.1&#x02013;4.2)</td>
</tr> <tr>
<td valign="top" align="left" colspan="13"><bold>Ischemic heart disease attributable to high temperature (1990 vs. 2021)</bold></td>
</tr> <tr>
<td valign="top" align="left">Global</td>
<td valign="top" align="center">20.18 (&#x02212;0.12, 51.93)</td>
<td valign="top" align="center">30.57 (5.41, 66.96)</td>
<td valign="top" align="center">0.51 (&#x02212;1.07, 3.9)</td>
<td valign="top" align="center">1.68 (1.33&#x02013;2.03)</td>
<td valign="top" align="center">15.44 (&#x02212;0.04, 39.55)</td>
<td valign="top" align="center">21.65 (3.91, 47.27)</td>
<td valign="top" align="center">0.40 (&#x02212;0.87, 4.41)</td>
<td valign="top" align="center">1.4 (1.04&#x02013;1.76)</td>
<td valign="top" align="center">25.6 (&#x02212;0.2, 65.26)</td>
<td valign="top" align="center">40.34 (7.01, 89.25)</td>
<td valign="top" align="center">0.58 (&#x02212;0.82, 3.94)</td>
<td valign="top" align="center">1.83 (1.48&#x02013;2.18)</td>
</tr> <tr>
<td valign="top" align="left">High SDI</td>
<td valign="top" align="center">10.29 (&#x02212;1.15, 35.64)</td>
<td valign="top" align="center">12.05 (0.95, 31.71)</td>
<td valign="top" align="center">0.17 (&#x02212;3.09, 6.06)</td>
<td valign="top" align="center">0.77 (0.4&#x02013;1.15)</td>
<td valign="top" align="center">6.75 (&#x02212;0.89, 24.01)</td>
<td valign="top" align="center">6.66 (0.4, 17.77)</td>
<td valign="top" align="center">&#x02212;0.01 (&#x02212;3.00, 4.47)</td>
<td valign="top" align="center">0.08 (&#x02212;0.31&#x02013;0.48)</td>
<td valign="top" align="center">14.67 (&#x02212;1.55, 50.16)</td>
<td valign="top" align="center">17.59 (1.46, 45.87)</td>
<td valign="top" align="center">0.20 (&#x02212;3.40, 5.70)</td>
<td valign="top" align="center">0.91 (0.53&#x02013;1.29)</td>
</tr> <tr>
<td valign="top" align="left">High-middle SDI</td>
<td valign="top" align="center">8.46 (&#x02212;3.53, 33.02)</td>
<td valign="top" align="center">12.67 (&#x02212;3.03, 43.09)</td>
<td valign="top" align="center">0.5 (&#x02212;3.02, 4.49)</td>
<td valign="top" align="center">1.02 (0.5&#x02013;1.55)</td>
<td valign="top" align="center">6.24 (&#x02212;2.64, 24.68)</td>
<td valign="top" align="center">8.98 (&#x02212;1.76, 31.54)</td>
<td valign="top" align="center">0.44 (&#x02212;3.06, 4.70)</td>
<td valign="top" align="center">0.87 (0.33&#x02013;1.42)</td>
<td valign="top" align="center">11.18 (&#x02212;4.55, 43.36)</td>
<td valign="top" align="center">16.93 (&#x02212;4.48, 58.32)</td>
<td valign="top" align="center">0.51 (&#x02212;3.24, 3.86)</td>
<td valign="top" align="center">1.1 (0.59&#x02013;1.61)</td>
</tr> <tr>
<td valign="top" align="left">Middle SDI</td>
<td valign="top" align="center">19.46 (&#x02212;2.17, 49.1)</td>
<td valign="top" align="center">31.05 (5.67, 68.28)</td>
<td valign="top" align="center">0.6 (&#x02212;8.72, 5.24)</td>
<td valign="top" align="center">1.7 (1.34&#x02013;2.05)</td>
<td valign="top" align="center">15.12 (&#x02212;2.44, 39.63)</td>
<td valign="top" align="center">22.03 (4.09, 47.72)</td>
<td valign="top" align="center">0.46 (&#x02212;8.49, 5.73)</td>
<td valign="top" align="center">1.44 (1.09&#x02013;1.8)</td>
<td valign="top" align="center">23.98 (&#x02212;1.83, 59.82)</td>
<td valign="top" align="center">41.03 (7.42, 89.32)</td>
<td valign="top" align="center">0.71 (&#x02212;8.14, 7.02)</td>
<td valign="top" align="center">1.9 (1.54&#x02013;2.26)</td>
</tr> <tr>
<td valign="top" align="left">Low-middle SDI</td>
<td valign="top" align="center">55.56 (7.38, 106.82)</td>
<td valign="top" align="center">78.49 (21.27, 148.31)</td>
<td valign="top" align="center">0.41 (0.15, 2.01)</td>
<td valign="top" align="center">1.65 (1.23&#x02013;2.07)</td>
<td valign="top" align="center">47.12 (5.43, 92.91)</td>
<td valign="top" align="center">58.14 (15.78, 107.87)</td>
<td valign="top" align="center">0.23 (&#x02212;0.02, 1.52)</td>
<td valign="top" align="center">1.16 (0.72&#x02013;1.6)</td>
<td valign="top" align="center">63.72 (9.29, 125.2)</td>
<td valign="top" align="center">100.33 (26.49, 192.02)</td>
<td valign="top" align="center">0.57 (0.27, 2.51)</td>
<td valign="top" align="center">2.03 (1.62&#x02013;2.45)</td>
</tr> <tr>
<td valign="top" align="left">Low SDI</td>
<td valign="top" align="center">24.9 (&#x02212;5.09, 58.76)</td>
<td valign="top" align="center">35.29 (5.17, 70.32)</td>
<td valign="top" align="center">0.42 (&#x02212;4.32, 6.66)</td>
<td valign="top" align="center">1.73 (1.22&#x02013;2.25)</td>
<td valign="top" align="center">22.3 (&#x02212;5.68, 53.08)</td>
<td valign="top" align="center">28.04 (3.77, 55.19)</td>
<td valign="top" align="center">0.26 (&#x02212;5.58, 3.67)</td>
<td valign="top" align="center">1.32 (0.81&#x02013;1.83)</td>
<td valign="top" align="center">27.4 (&#x02212;5.22, 65.2)</td>
<td valign="top" align="center">42.96 (6.69, 85.62)</td>
<td valign="top" align="center">0.57 (&#x02212;4.56, 6.29)</td>
<td valign="top" align="center">2.08 (1.55&#x02013;2.6)</td>
</tr> <tr>
<td valign="top" align="left" colspan="13"><bold>Myocardial disease attributable to low temperature (1990 vs. 2021)</bold></td>
</tr> <tr>
<td valign="top" align="left">Global</td>
<td valign="top" align="center">11.61 (9.15, 14.37)</td>
<td valign="top" align="center">7.01 (5.35, 9.03)</td>
<td valign="top" align="center">&#x02212;0.40 (&#x02212;0.47, &#x02212;0.31)</td>
<td valign="top" align="center">&#x02212;1.87 (&#x02212;2.17&#x02013;1.58)</td>
<td valign="top" align="center">8.95 (6.89, 11.60)</td>
<td valign="top" align="center">4.49 (3.33, 5.99)</td>
<td valign="top" align="center">&#x02212;0.50 (&#x02212;0.57, &#x02212;0.41)</td>
<td valign="top" align="center">&#x02212;2.38 (&#x02212;2.59&#x02013;2.16)</td>
<td valign="top" align="center">14.37 (11.36, 17.45)</td>
<td valign="top" align="center">9.64 (7.36, 12.27)</td>
<td valign="top" align="center">&#x02212;0.51 (&#x02212;0.55, &#x02212;0.48)</td>
<td valign="top" align="center">&#x02212;1.58 (&#x02212;1.92&#x02013;1.24)</td>
</tr> <tr>
<td valign="top" align="left">High SDI</td>
<td valign="top" align="center">15.44 (12.11, 17.61)</td>
<td valign="top" align="center">7.17 (5.71, 8.16)</td>
<td valign="top" align="center">&#x02212;0.54 (&#x02212;0.57, &#x02212;0.50)</td>
<td valign="top" align="center">&#x02212;2.92 (&#x02212;3.07&#x02013;2.76)</td>
<td valign="top" align="center">10.62 (8.25, 12.13)</td>
<td valign="top" align="center">4.31 (3.42, 4.94)</td>
<td valign="top" align="center">&#x02212;0.59 (&#x02212;0.63, &#x02212;0.55)</td>
<td valign="top" align="center">&#x02212;3.31 (&#x02212;3.46&#x02013;3.16)</td>
<td valign="top" align="center">20.92 (16.47, 23.80)</td>
<td valign="top" align="center">10.17 (8.14, 11.53)</td>
<td valign="top" align="center">&#x02212;0.51 (&#x02212;0.55, &#x02212;0.48)</td>
<td valign="top" align="center">&#x02212;2.8 (&#x02212;2.96&#x02013;2.64)</td>
</tr> <tr>
<td valign="top" align="left">Middle-high SDI</td>
<td valign="top" align="center">18.14 (13.55, 20.96)</td>
<td valign="top" align="center">13.61 (10.52, 16.42)</td>
<td valign="top" align="center">&#x02212;0.25 (&#x02212;0.34, &#x02212;0.14)</td>
<td valign="top" align="center">&#x02212;1.21 (&#x02212;1.87&#x02013;0.54)</td>
<td valign="top" align="center">13.12 (9.61, 15.50)</td>
<td valign="top" align="center">7.45 (5.58, 9.29)</td>
<td valign="top" align="center">&#x02212;0.43 (&#x02212;0.52, &#x02212;0.31)</td>
<td valign="top" align="center">&#x02212;2.03 (&#x02212;2.57&#x02013;1.48)</td>
<td valign="top" align="center">23.72 (17.54, 27.51)</td>
<td valign="top" align="center">19.87 (15.29, 24.31)</td>
<td valign="top" align="center">&#x02212;0.16 (&#x02212;0.27, &#x02212;0.04)</td>
<td valign="top" align="center">&#x02212;0.89 (&#x02212;1.61&#x02013;0.17)</td>
</tr> <tr>
<td valign="top" align="left">Middle SDI</td>
<td valign="top" align="center">5.97 (4.07, 8.44)</td>
<td valign="top" align="center">3.62 (2.40, 5.05)</td>
<td valign="top" align="center">&#x02212;0.39 (&#x02212;0.53, &#x02212;0.26)</td>
<td valign="top" align="center">&#x02212;1.88 (&#x02212;2.1&#x02013;1.66)</td>
<td valign="top" align="center">5.10 (3.33, 7.33)</td>
<td valign="top" align="center">2.55 (1.69, 3.59)</td>
<td valign="top" align="center">&#x02212;0.50 (&#x02212;0.63, &#x02212;0.29)</td>
<td valign="top" align="center">&#x02212;2.38 (&#x02212;2.63&#x02013;2.14)</td>
<td valign="top" align="center">6.83 (4.68, 9.66)</td>
<td valign="top" align="center">4.72 (3.06, 6.67)</td>
<td valign="top" align="center">&#x02212;0.31 (&#x02212;0.49, &#x02212;0.15)</td>
<td valign="top" align="center">&#x02212;1.51 (&#x02212;1.72&#x02013;1.3)</td>
</tr> <tr>
<td valign="top" align="left">Middle-low SDI</td>
<td valign="top" align="center">6.52 (1.99, 12.15)</td>
<td valign="top" align="center">5.79 (2.06, 10.00)</td>
<td valign="top" align="center">&#x02212;0.11 (&#x02212;0.30, 0.22)</td>
<td valign="top" align="center">&#x02212;0.34 (&#x02212;0.6&#x02013;0.07)</td>
<td valign="top" align="center">5.40 (1.48, 10.86)</td>
<td valign="top" align="center">4.18 (1.33, 7.54)</td>
<td valign="top" align="center">&#x02212;0.23 (&#x02212;0.41, 0.28)</td>
<td valign="top" align="center">&#x02212;0.66 (&#x02212;0.93&#x02013;0.38)</td>
<td valign="top" align="center">7.61 (2.34, 14.87)</td>
<td valign="top" align="center">7.52 (2.78, 13.18)</td>
<td valign="top" align="center">&#x02212;0.01 (&#x02212;0.24, 0.34)</td>
<td valign="top" align="center">&#x02212;0.07 (&#x02212;0.34&#x02013;0.2)</td>
</tr> <tr>
<td valign="top" align="left">Low SDI</td>
<td valign="top" align="center">6.45 (2.70, 11.91)</td>
<td valign="top" align="center">5.08 (2.33, 8.98)</td>
<td valign="top" align="center">&#x02212;0.21 (&#x02212;0.41, 0.26)</td>
<td valign="top" align="center">&#x02212;0.88 (&#x02212;1.21&#x02013;0.55)</td>
<td valign="top" align="center">5.29 (1.67, 10.63)</td>
<td valign="top" align="center">3.71 (1.50, 6.74)</td>
<td valign="top" align="center">&#x02212;0.30 (&#x02212;0.49, 0.29)</td>
<td valign="top" align="center">&#x02212;1.18 (&#x02212;1.53 to &#x02212;0.84)</td>
<td valign="top" align="center">7.58 (2.97, 14.72)</td>
<td valign="top" align="center">6.51 (2.93, 12.15)</td>
<td valign="top" align="center">&#x02212;0.14 (&#x02212;0.37, 0.39)</td>
<td valign="top" align="center">&#x02212;0.64 (&#x02212;0.96 to &#x02212;0.32)</td>
</tr> <tr>
<td valign="top" align="left" colspan="13"><bold>Ischemic heart disease attributable to low temperature (1990 vs. 2021)</bold></td>
</tr> <tr>
<td valign="top" align="left">Global</td>
<td valign="top" align="center">183.27 (161.52, 219.62)</td>
<td valign="top" align="center">117.39 (101.19, 144.86)</td>
<td valign="top" align="center">&#x02212;0.36 (&#x02212;0.4, &#x02212;0.32)</td>
<td valign="top" align="center">&#x02212;1.73 (&#x02212;1.85&#x02013;1.6)</td>
<td valign="top" align="center">142.15 (123.20, 170.66)</td>
<td valign="top" align="center">84.77 (72.13, 103.94)</td>
<td valign="top" align="center">&#x02212;0.40 (&#x02212;0.45, &#x02212;0.36)</td>
<td valign="top" align="center">&#x02212;1.98 (&#x02212;2.1&#x02013;1.86)</td>
<td valign="top" align="center">228.30 (201.97, 274.55)</td>
<td valign="top" align="center">153.52 (131.79, 186.38)</td>
<td valign="top" align="center">&#x02212;0.33 (&#x02212;0.38, &#x02212;0.27)</td>
<td valign="top" align="center">&#x02212;1.55 (&#x02212;1.67&#x02013;1.42)</td>
</tr> <tr>
<td valign="top" align="left">High SDI</td>
<td valign="top" align="center">187.15 (168.11, 224.88)</td>
<td valign="top" align="center">72.05 (63.42, 86.78)</td>
<td valign="top" align="center">&#x02212;0.61 (&#x02212;0.63, &#x02212;0.6)</td>
<td valign="top" align="center">&#x02212;3.51 (&#x02212;3.66&#x02013;3.37)</td>
<td valign="top" align="center">123.38 (108.26, 148.94)</td>
<td valign="top" align="center">43.63 (36.54, 52.71)</td>
<td valign="top" align="center">&#x02212;0.65 (&#x02212;0.66, &#x02212;0.63)</td>
<td valign="top" align="center">&#x02212;3.85 (&#x02212;3.99&#x02013;3.7)</td>
<td valign="top" align="center">266.70 (243.18, 318.54)</td>
<td valign="top" align="center">103.33 (92.46, 123.28)</td>
<td valign="top" align="center">&#x02212;0.61 (&#x02212;0.63, &#x02212;0.60)</td>
<td valign="top" align="center">&#x02212;3.46 (&#x02212;3.61&#x02013;3.31)</td>
</tr> <tr>
<td valign="top" align="left">Middle-high SDI</td>
<td valign="top" align="center">236.99 (213.64, 281.68)</td>
<td valign="top" align="center">146.37 (127.31, 178.50)</td>
<td valign="top" align="center">&#x02212;0.38 (&#x02212;0.43, &#x02212;0.33)</td>
<td valign="top" align="center">&#x02212;2.09 (&#x02212;2.37&#x02013;1.81)</td>
<td valign="top" align="center">179.37 (160.40, 213.64)</td>
<td valign="top" align="center">107.65 (90.19, 133.69)</td>
<td valign="top" align="center">&#x02212;0.40 (&#x02212;0.46, &#x02212;0.33)</td>
<td valign="top" align="center">&#x02212;2.19 (&#x02212;2.47&#x02013;1.92)</td>
<td valign="top" align="center">304.15 (272.95, 362.23)</td>
<td valign="top" align="center">190.13 (164.90, 232.67)</td>
<td valign="top" align="center">&#x02212;0.37 (&#x02212;0.44, &#x02212;0.31)</td>
<td valign="top" align="center">&#x02212;2.01 (&#x02212;2.29&#x02013;1.74)</td>
</tr> <tr>
<td valign="top" align="left">Middle SDI</td>
<td valign="top" align="center">143.31 (118.77, 172.53)</td>
<td valign="top" align="center">119.00 (101.56, 142.01)</td>
<td valign="top" align="center">&#x02212;0.17 (&#x02212;0.26, &#x02212;0.07)</td>
<td valign="top" align="center">&#x02212;0.63 (&#x02212;0.78&#x02013;0.48)</td>
<td valign="top" align="center">118.26 (97.45, 143.45)</td>
<td valign="top" align="center">85.76 (71.70, 103.04)</td>
<td valign="top" align="center">&#x02212;0.27 (&#x02212;0.37, &#x02212;0.16)</td>
<td valign="top" align="center">&#x02212;1.06 (&#x02212;1.21&#x02013;0.92)</td>
<td valign="top" align="center">169.16 (138.84, 204.69)</td>
<td valign="top" align="center">156.58 (132.66, 187.73)</td>
<td valign="top" align="center">&#x02212;0.07 (&#x02212;0.20, 0.07)</td>
<td valign="top" align="center">&#x02212;0.27 (&#x02212;0.43&#x02013;0.12)</td>
</tr> <tr>
<td valign="top" align="left">Middle-low SDI</td>
<td valign="top" align="center">150.20 (111.81, 192.41)</td>
<td valign="top" align="center">137.92 (104.50, 178.71)</td>
<td valign="top" align="center">&#x02212;0.08 (&#x02212;0.17, 0.02)</td>
<td valign="top" align="center">&#x02212;0.27 (&#x02212;0.5&#x02013;0.05)</td>
<td valign="top" align="center">128.43 (94.06, 168.00)</td>
<td valign="top" align="center">102.49 (76.62, 131.85)</td>
<td valign="top" align="center">&#x02212;0.20 (&#x02212;0.30, &#x02212;0.10)</td>
<td valign="top" align="center">&#x02212;0.73 (&#x02212;0.96&#x02013;0.5)</td>
<td valign="top" align="center">171.01 (123.67, 220.66)</td>
<td valign="top" align="center">175.87 (132.24, 231.11)</td>
<td valign="top" align="center">0.03 (&#x02212;0.10, 0.18)</td>
<td valign="top" align="center">0.1 (&#x02212;0.13&#x02013;0.33)</td>
</tr> <tr>
<td valign="top" align="left">Low SDI</td>
<td valign="top" align="center">119.02 (91.61, 151.98)</td>
<td valign="top" align="center">100.39 (78.76, 124.51)</td>
<td valign="top" align="center">&#x02212;0.16 (&#x02212;0.26, &#x02212;0.04)</td>
<td valign="top" align="center">&#x02212;0.64 (&#x02212;0.91&#x02013;0.37)</td>
<td valign="top" align="center">102.33 (75.38, 131.64)</td>
<td valign="top" align="center">76.89 (59.26, 95.72)</td>
<td valign="top" align="center">0.25 (&#x02212;0.35, &#x02212;0.12)</td>
<td valign="top" align="center">&#x02212;1.02 (&#x02212;1.31&#x02013;0.73)</td>
<td valign="top" align="center">135.15 (102.21, 172.82)</td>
<td valign="top" align="center">125.23 (97.98, 157.59)</td>
<td valign="top" align="center">0.07 (&#x02212;0.22, 0.09)</td>
<td valign="top" align="center">&#x02212;0.32 (&#x02212;0.58&#x02013;0.06)</td>
</tr> <tr>
<td valign="top" align="left" colspan="13"><bold>Myocardial disease attributable to high temperature (1990 vs. 2021)</bold></td>
</tr> <tr>
<td valign="top" align="left">Global</td>
<td valign="top" align="center">0.05 (&#x02212;0.03, 0.14)</td>
<td valign="top" align="center">0.06 (&#x02212;0.02, 0.15)</td>
<td valign="top" align="center">0.25 (&#x02212;0.68, 1.75)</td>
<td valign="top" align="center">1.35 (0.86&#x02013;1.85)</td>
<td valign="top" align="center">0.04 (&#x02212;0.02, 0.12)</td>
<td valign="top" align="center">0.05 (&#x02212;0.02, 0.11)</td>
<td valign="top" align="center">0.12 (&#x02212;0.84, 1.34)</td>
<td valign="top" align="center">1.1 (0.61&#x02013;1.6)</td>
<td valign="top" align="center">0.06 (&#x02212;0.03, 0.18)</td>
<td valign="top" align="center">0.08 (&#x02212;0.03, 0.21)</td>
<td valign="top" align="center">0.33 (&#x02212;0.78, 2.14)</td>
<td valign="top" align="center">1.48 (0.98&#x02013;1.98)</td>
</tr> <tr>
<td valign="top" align="left">High SDI</td>
<td valign="top" align="center">0.05 (&#x02212;0.01, 0.13)</td>
<td valign="top" align="center">0.04 (&#x02212;0.01, 0.09)</td>
<td valign="top" align="center">&#x02212;0.28 (&#x02212;0.75, 0.03)</td>
<td valign="top" align="center">&#x02212;0.43 (&#x02212;0.92&#x02013;0.05)</td>
<td valign="top" align="center">0.04 (&#x02212;0.01, 0.09)</td>
<td valign="top" align="center">0.03 (&#x02212;0.00, 0.06)</td>
<td valign="top" align="center">&#x02212;0.36 (&#x02212;0.76, &#x02212;0.07)</td>
<td valign="top" align="center">&#x02212;0.73 (&#x02212;1.23&#x02013;&#x02212;0.24)</td>
<td valign="top" align="center">0.07 (&#x02212;0.02, 0.18)</td>
<td valign="top" align="center">0.05 (&#x02212;0.01, 0.12)</td>
<td valign="top" align="center">&#x02212;0.27 (&#x02212;0.75, 0.08)</td>
<td valign="top" align="center">&#x02212;0.42 (&#x02212;0.9&#x02013;0.06)</td>
</tr> <tr>
<td valign="top" align="left">High-middle SDI</td>
<td valign="top" align="center">0.03 (&#x02212;0.02, 0.10)</td>
<td valign="top" align="center">0.05 (&#x02212;0.03, 0.12)</td>
<td valign="top" align="center">0.36 (&#x02212;0.65, 1.26)</td>
<td valign="top" align="center">0.62 (&#x02212;0.12&#x02013;1.36)</td>
<td valign="top" align="center">0.03 (&#x02212;0.02, 0.09)</td>
<td valign="top" align="center">0.03 (&#x02212;0.02, 0.08)</td>
<td valign="top" align="center">0.09 (&#x02212;0.69, 1.16)</td>
<td valign="top" align="center">&#x02212;0.11 (&#x02212;0.83&#x02013;0.61)</td>
<td valign="top" align="center">0.04 (&#x02212;0.03, 0.13)</td>
<td valign="top" align="center">0.06 (&#x02212;0.04, 0.17)</td>
<td valign="top" align="center">0.52 (&#x02212;0.99, 1.43)</td>
<td valign="top" align="center">0.99 (0.25&#x02013;1.73)</td>
</tr> <tr>
<td valign="top" align="left">Middle SDI</td>
<td valign="top" align="center">0.04 (&#x02212;0.02, 0.13)</td>
<td valign="top" align="center">0.06 (&#x02212;0.01, 0.12)</td>
<td valign="top" align="center">1.05 (&#x02212;8.54, 13.22)</td>
<td valign="top" align="center">1.39 (0.94&#x02013;1.85)</td>
<td valign="top" align="center">0.04 (&#x02212;0.02, 0.09)</td>
<td valign="top" align="center">0.04 (&#x02212;0.01, 0.10)</td>
<td valign="top" align="center">0.84 (&#x02212;11.59, 6.60)</td>
<td valign="top" align="center">1.03 (0.57&#x02013;1.5)</td>
<td valign="top" align="center">0.05 (&#x02212;0.02, 0.13)</td>
<td valign="top" align="center">0.07 (&#x02212;0.02, 0.16)</td>
<td valign="top" align="center">1.25 (&#x02212;7.54, 9.36)</td>
<td valign="top" align="center">1.7 (1.26&#x02013;2.15)</td>
</tr> <tr>
<td valign="top" align="left">Low-middle SDI</td>
<td valign="top" align="center">0.08 (&#x02212;0.06, 0.33)</td>
<td valign="top" align="center">0.14 (&#x02212;0.05, 0.35)</td>
<td valign="top" align="center">0.62 (&#x02212;3.36, 5.54)</td>
<td valign="top" align="center">2.28 (1.61&#x02013;2.96)</td>
<td valign="top" align="center">0.07 (&#x02212;0.04, 0.22)</td>
<td valign="top" align="center">0.10 (&#x02212;0.03, 0.25)</td>
<td valign="top" align="center">0.52 (&#x02212;6.41, 14.51)</td>
<td valign="top" align="center">2.23 (1.53&#x02013;2.93)</td>
<td valign="top" align="center">0.10 (&#x02212;0.06, 0.33)</td>
<td valign="top" align="center">0.18 (&#x02212;0.07, 0.47)</td>
<td valign="top" align="center">0.73 (&#x02212;2.98, 5.15)</td>
<td valign="top" align="center">2.4 (1.74&#x02013;3.06)</td>
</tr> <tr>
<td valign="top" align="left">Low SDI</td>
<td valign="top" align="center">0.05 (&#x02212;0.10, 0.32)</td>
<td valign="top" align="center">0.10 (&#x02212;0.08, 0.32)</td>
<td valign="top" align="center">0.33 (&#x02212;2.08, 2.72)</td>
<td valign="top" align="center">3.4 (2.33&#x02013;4.48)</td>
<td valign="top" align="center">0.04 (&#x02212;0.08, 0.24)</td>
<td valign="top" align="center">0.08 (&#x02212;0.05, 0.23)</td>
<td valign="top" align="center">0.15 (&#x02212;1.97, 2.35)</td>
<td valign="top" align="center">3.03 (1.97&#x02013;4.1)</td>
<td valign="top" align="center">0.06 (&#x02212;0.12, 0.33)</td>
<td valign="top" align="center">0.12 (&#x02212;0.11, 0.42)</td>
<td valign="top" align="center">0.49 (&#x02212;1.59, 4.03)</td>
<td valign="top" align="center">3.71 (2.62&#x02013;4.83)</td>
</tr> <tr>
<td valign="top" align="left" colspan="13"><bold>Ischemic heart disease attributable to high temperature (1990 vs. 2021)</bold></td>
</tr> <tr>
<td valign="top" align="left">Global</td>
<td valign="top" align="center">0.90 (&#x02212;0.03, 2.46)</td>
<td valign="top" align="center">1.34 (0.20, 3.07)</td>
<td valign="top" align="center">0.48 (&#x02212;1.96, 4.76)</td>
<td valign="top" align="center">1.66 (1.31&#x02013;2)</td>
<td valign="top" align="center">0.72 (&#x02212;0.04, 1.99)</td>
<td valign="top" align="center">1.00 (0.15, 2.32)</td>
<td valign="top" align="center">0.39 (&#x02212;2.29, 4.59)</td>
<td valign="top" align="center">1.43 (1.08&#x02013;1.79)</td>
<td valign="top" align="center">1.14 (&#x02212;0.02, 3.01)</td>
<td valign="top" align="center">1.74 (0.26, 4.01)</td>
<td valign="top" align="center">0.52 (&#x02212;1.59, 4.71)</td>
<td valign="top" align="center">1.78 (1.44&#x02013;2.13)</td>
</tr> <tr>
<td valign="top" align="left">High SDI</td>
<td valign="top" align="center">0.53 (&#x02212;0.08, 1.89)</td>
<td valign="top" align="center">0.45 (&#x02212;0.00, 1.31)</td>
<td valign="top" align="center">&#x02212;0.14 (&#x02212;2.91, 3.65)</td>
<td valign="top" align="center">&#x02212;0.25 (&#x02212;0.67&#x02013;0.16)</td>
<td valign="top" align="center">0.39 (&#x02212;0.06, 1.43)</td>
<td valign="top" align="center">0.28 (&#x02212;0.01, 0.85)</td>
<td valign="top" align="center">&#x02212;0.28 (&#x02212;2.21, 2.69)</td>
<td valign="top" align="center">&#x02212;0.86 (&#x02212;1.3 to &#x02212;0.42)</td>
<td valign="top" align="center">0.72 (&#x02212;0.10, 2.55)</td>
<td valign="top" align="center">0.64 (0.00, 1.83)</td>
<td valign="top" align="center">&#x02212;0.11 (&#x02212;2.46, 4.00)</td>
<td valign="top" align="center">&#x02212;0.1 (&#x02212;0.51&#x02013;0.31)</td>
</tr> <tr>
<td valign="top" align="left">High-middle SDI</td>
<td valign="top" align="center">0.44 (&#x02212;0.18, 1.76)</td>
<td valign="top" align="center">0.70 (&#x02212;0.18, 2.45)</td>
<td valign="top" align="center">0.61 (&#x02212;2.81, 4.69)</td>
<td valign="top" align="center">1.3 (0.77&#x02013;1.83)</td>
<td valign="top" align="center">0.35 (&#x02212;0.14, 1.45)</td>
<td valign="top" align="center">0.56 (&#x02212;0.12, 2.01)</td>
<td valign="top" align="center">0.57 (&#x02212;3.31, 5.22)</td>
<td valign="top" align="center">1.15 (0.6&#x02013;1.7)</td>
<td valign="top" align="center">0.55 (&#x02212;0.22, 2.18)</td>
<td valign="top" align="center">0.89 (&#x02212;0.26, 3.15)</td>
<td valign="top" align="center">0.62 (&#x02212;2.43, 4.25)</td>
<td valign="top" align="center">1.41 (0.91&#x02013;1.92)</td>
</tr> <tr>
<td valign="top" align="left">Middle SDI</td>
<td valign="top" align="center">0.92 (&#x02212;0.13, 2.40)</td>
<td valign="top" align="center">1.51 (0.24, 3.47)</td>
<td valign="top" align="center">0.64 (&#x02212;6.96, 5.7)</td>
<td valign="top" align="center">1.88 (1.53&#x02013;2.23)</td>
<td valign="top" align="center">0.76 (&#x02212;0.15, 2.07)</td>
<td valign="top" align="center">1.15 (0.18, 2.61)</td>
<td valign="top" align="center">0.51 (&#x02212;7.16, 5.63)</td>
<td valign="top" align="center">1.66 (1.31&#x02013;2.01)</td>
<td valign="top" align="center">1.11 (&#x02212;0.11, 2.82)</td>
<td valign="top" align="center">1.96 (0.29, 4.43)</td>
<td valign="top" align="center">0.77 (&#x02212;9.91, 4.89)</td>
<td valign="top" align="center">2.1 (1.75&#x02013;2.44)</td>
</tr> <tr>
<td valign="top" align="left">Low-middle SDI</td>
<td valign="top" align="center">2.42 (0.29, 4.71)</td>
<td valign="top" align="center">3.49 (0.96, 6.57)</td>
<td valign="top" align="center">0.44 (0.19, 2.04)</td>
<td valign="top" align="center">1.77 (1.35&#x02013;2.19)</td>
<td valign="top" align="center">2.12 (0.22, 4.23)</td>
<td valign="top" align="center">2.71 (0.74, 5.02)</td>
<td valign="top" align="center">0.28 (0.03, 1.61)</td>
<td valign="top" align="center">1.32 (0.88&#x02013;1.76)</td>
<td valign="top" align="center">2.72 (0.35, 5.37)</td>
<td valign="top" align="center">4.37 (1.18, 8.38)</td>
<td valign="top" align="center">0.61 (0.31, 2.48)</td>
<td valign="top" align="center">2.18 (1.76&#x02013;2.6)</td>
</tr> <tr>
<td valign="top" align="left">Low SDI</td>
<td valign="top" align="center">1.13 (&#x02212;0.26, 2.68)</td>
<td valign="top" align="center">1.71 (0.26, 3.36)</td>
<td valign="top" align="center">0.51 (&#x02212;5.61, 8.01)</td>
<td valign="top" align="center">2.15 (1.61&#x02013;2.7)</td>
<td valign="top" align="center">1.04 (&#x02212;0.31, 2.52)</td>
<td valign="top" align="center">1.39 (0.19, 2.74)</td>
<td valign="top" align="center">0.33 (&#x02212;4.42, 5.73)</td>
<td valign="top" align="center">1.7 (1.15&#x02013;2.25)</td>
<td valign="top" align="center">1.22 (&#x02212;0.24, 2.93)</td>
<td valign="top" align="center">2.06 (0.35, 4.09)</td>
<td valign="top" align="center">0.69 (&#x02212;5.08, 7.56)</td>
<td valign="top" align="center">2.56 (2&#x02013;3.12)</td>
</tr> <tr>
<td valign="top" align="left" colspan="13"><bold>Myocardial disease attributable to low temperature (1990 vs. 2021)</bold></td>
</tr> <tr>
<td valign="top" align="left">Global</td>
<td valign="top" align="center">0.52 (0.40, 0.61)</td>
<td valign="top" align="center">0.27 (0.21, 0.34)</td>
<td valign="top" align="center">&#x02212;0.47 (&#x02212;0.53, &#x02212;0.41)</td>
<td valign="top" align="center">&#x02212;2.34 (&#x02212;2.52&#x02013;2.15)</td>
<td valign="top" align="center">0.44 (0.34, 0.52)</td>
<td valign="top" align="center">0.19 (0.15, 0.24)</td>
<td valign="top" align="center">&#x02212;0.56 (&#x02212;0.62, &#x02212;0.50)</td>
<td valign="top" align="center">&#x02212;2.84 (&#x02212;2.99&#x02013;2.7)</td>
<td valign="top" align="center">0.60 (0.48, 0.71)</td>
<td valign="top" align="center">0.36 (0.28, 0.44)</td>
<td valign="top" align="center">&#x02212;0.40 (&#x02212;0.46, &#x02212;0.33)</td>
<td valign="top" align="center">&#x02212;1.96 (&#x02212;2.17&#x02013;1.74)</td>
</tr> <tr>
<td valign="top" align="left">High SDI</td>
<td valign="top" align="center">0.65 (0.51, 0.73)</td>
<td valign="top" align="center">0.30 (0.23, 0.34)</td>
<td valign="top" align="center">&#x02212;0.46 (&#x02212;0.52, &#x02212;0.37)</td>
<td valign="top" align="center">&#x02212;2.93 (&#x02212;3.08&#x02013;2.78)</td>
<td valign="top" align="center">0.49 (0.39, 0.56)</td>
<td valign="top" align="center">0.20 (0.15, 0.23)</td>
<td valign="top" align="center">&#x02212;0.57 (&#x02212;0.63, &#x02212;0.49)</td>
<td valign="top" align="center">&#x02212;3.27 (&#x02212;3.43&#x02013;3.12)</td>
<td valign="top" align="center">0.84 (0.66, 0.95)</td>
<td valign="top" align="center">0.41 (0.32, 0.46)</td>
<td valign="top" align="center">&#x02212;0.39 (&#x02212;0.46, &#x02212;0.30)</td>
<td valign="top" align="center">&#x02212;2.8 (&#x02212;2.95&#x02013;2.64)</td>
</tr> <tr>
<td valign="top" align="left">High-middle SDI</td>
<td valign="top" align="center">0.87 (0.63, 1.01)</td>
<td valign="top" align="center">0.47 (0.36, 0.56)</td>
<td valign="top" align="center">&#x02212;0.54 (&#x02212;0.57, &#x02212;0.51)</td>
<td valign="top" align="center">&#x02212;2.22 (&#x02212;2.66&#x02013;1.79)</td>
<td valign="top" align="center">0.72 (0.52, 0.85)</td>
<td valign="top" align="center">0.31 (0.23, 0.38)</td>
<td valign="top" align="center">&#x02212;0.59 (&#x02212;0.62, &#x02212;0.55)</td>
<td valign="top" align="center">&#x02212;2.97 (&#x02212;3.3&#x02013;2.63)</td>
<td valign="top" align="center">1.05 (0.78, 1.23)</td>
<td valign="top" align="center">0.64 (0.50, 0.77)</td>
<td valign="top" align="center">&#x02212;0.51 (&#x02212;0.55, &#x02212;0.48)</td>
<td valign="top" align="center">&#x02212;1.85 (&#x02212;2.34&#x02013;1.36)</td>
</tr> <tr>
<td valign="top" align="left">Middle SDI</td>
<td valign="top" align="center">0.20 (0.13, 0.29)</td>
<td valign="top" align="center">0.13 (0.09, 0.19)</td>
<td valign="top" align="center">&#x02212;0.06 (&#x02212;0.25, 0.29)</td>
<td valign="top" align="center">&#x02212;1.52 (&#x02212;1.78&#x02013;1.26)</td>
<td valign="top" align="center">0.17 (0.11, 0.25)</td>
<td valign="top" align="center">0.10 (0.06, 0.15)</td>
<td valign="top" align="center">&#x02212;0.16 (&#x02212;0.37, 0.33)</td>
<td valign="top" align="center">&#x02212;1.93 (&#x02212;2.23&#x02013;1.63)</td>
<td valign="top" align="center">0.22 (0.15, 0.33)</td>
<td valign="top" align="center">0.17 (0.11, 0.24)</td>
<td valign="top" align="center">0.04 (&#x02212;0.20, 0.43)</td>
<td valign="top" align="center">&#x02212;1.15 (&#x02212;1.38&#x02013;0.92)</td>
</tr> <tr>
<td valign="top" align="left">Low-middle SDI</td>
<td valign="top" align="center">0.23 (0.07, 0.45)</td>
<td valign="top" align="center">0.22 (0.07, 0.37)</td>
<td valign="top" align="center">&#x02212;0.12 (&#x02212;0.33, 0.37)</td>
<td valign="top" align="center">&#x02212;0.17 (&#x02212;0.45&#x02013;0.11)</td>
<td valign="top" align="center">0.19 (0.05, 0.38)</td>
<td valign="top" align="center">0.16 (0.05, 0.28)</td>
<td valign="top" align="center">&#x02212;0.18 (&#x02212;0.41, 0.52)</td>
<td valign="top" align="center">&#x02212;0.43 (&#x02212;0.71&#x02013;0.16)</td>
<td valign="top" align="center">0.27 (0.08, 0.54)</td>
<td valign="top" align="center">0.28 (0.10, 0.51)</td>
<td valign="top" align="center">&#x02212;0.07 (&#x02212;0.30, 0.43)</td>
<td valign="top" align="center">0.09 (&#x02212;0.2&#x02013;0.37)</td>
</tr> <tr>
<td valign="top" align="left">Low SDI</td>
<td valign="top" align="center">0.23 (0.09, 0.45)</td>
<td valign="top" align="center">0.20 (0.09, 0.36)</td>
<td valign="top" align="center">&#x02212;0.32 (&#x02212;0.51, &#x02212;0.15)</td>
<td valign="top" align="center">&#x02212;0.38 (&#x02212;0.77&#x02013;0)</td>
<td valign="top" align="center">0.19 (0.06, 0.40)</td>
<td valign="top" align="center">0.15 (0.06, 0.29)</td>
<td valign="top" align="center">&#x02212;0.41 (&#x02212;0.60, &#x02212;0.19)</td>
<td valign="top" align="center">&#x02212;0.55 (&#x02212;0.97&#x02013;0.14)</td>
<td valign="top" align="center">0.27 (0.11, 0.55)</td>
<td valign="top" align="center">0.25 (0.11, 0.49)</td>
<td valign="top" align="center">&#x02212;0.23 (&#x02212;0.43, &#x02212;0.05)</td>
<td valign="top" align="center">&#x02212;0.22 (&#x02212;0.58&#x02013;0.15)</td>
</tr> <tr>
<td valign="top" align="left" colspan="13"><bold>Ischemic heart disease attributable to low temperature (1990 vs. 2021)</bold></td>
</tr> <tr>
<td valign="top" align="left">Global</td>
<td valign="top" align="center">9.74 (8.52, 11.60)</td>
<td valign="top" align="center">6.14 (5.23, 7.53)</td>
<td valign="top" align="center">&#x02212;0.37 (&#x02212;0.4, &#x02212;0.33)</td>
<td valign="top" align="center">&#x02212;1.76 (&#x02212;1.88&#x02013;1.64)</td>
<td valign="top" align="center">8.28 (7.10, 9.86)</td>
<td valign="top" align="center">4.85 (4.05, 5.97)</td>
<td valign="top" align="center">&#x02212;0.41 (&#x02212;0.46, &#x02212;0.37)</td>
<td valign="top" align="center">&#x02212;2.03 (&#x02212;2.15&#x02013;1.92)</td>
<td valign="top" align="center">11.45 (10.10, 13.75)</td>
<td valign="top" align="center">7.71 (6.60, 9.29)</td>
<td valign="top" align="center">&#x02212;0.33 (&#x02212;0.38, &#x02212;0.27)</td>
<td valign="top" align="center">&#x02212;1.5 (&#x02212;1.62&#x02013;1.38)</td>
</tr> <tr>
<td valign="top" align="left">High SDI</td>
<td valign="top" align="center">10.27 (9.00, 12.35)</td>
<td valign="top" align="center">3.84 (3.21, 4.60)</td>
<td valign="top" align="center">&#x02212;0.63 (&#x02212;0.64, &#x02212;0.61)</td>
<td valign="top" align="center">&#x02212;3.66 (&#x02212;3.8&#x02013;3.51)</td>
<td valign="top" align="center">7.74 (6.56, 9.32)</td>
<td valign="top" align="center">2.67 (2.12, 3.25)</td>
<td valign="top" align="center">&#x02212;0.65 (&#x02212;0.68, &#x02212;0.64)</td>
<td valign="top" align="center">&#x02212;3.95 (&#x02212;4.1&#x02013;3.8)</td>
<td valign="top" align="center">13.84 (12.40, 16.58)</td>
<td valign="top" align="center">5.25 (4.56, 6.24)</td>
<td valign="top" align="center">&#x02212;0.62 (&#x02212;0.64, &#x02212;0.61)</td>
<td valign="top" align="center">&#x02212;3.59 (&#x02212;3.74&#x02013;3.44)</td>
</tr> <tr>
<td valign="top" align="left">High-middle SDI</td>
<td valign="top" align="center">13.03 (11.64, 15.52)</td>
<td valign="top" align="center">8.42 (7.17, 10.32)</td>
<td valign="top" align="center">&#x02212;0.35 (&#x02212;0.4, &#x02212;0.3)</td>
<td valign="top" align="center">&#x02212;1.85 (&#x02212;2.08&#x02013;1.62)</td>
<td valign="top" align="center">11.11 (9.85, 13.25)</td>
<td valign="top" align="center">6.97 (5.70, 8.68)</td>
<td valign="top" align="center">&#x02212;0.37 (&#x02212;0.43, &#x02212;0.31)</td>
<td valign="top" align="center">&#x02212;1.98 (&#x02212;2.21&#x02013;1.75)</td>
<td valign="top" align="center">15.50 (13.88, 18.37)</td>
<td valign="top" align="center">10.25 (8.85, 12.46)</td>
<td valign="top" align="center">&#x02212;0.34 (&#x02212;0.41, &#x02212;0.28)</td>
<td valign="top" align="center">&#x02212;1.71 (&#x02212;1.94&#x02013;1.48)</td>
</tr> <tr>
<td valign="top" align="left">Middle SDI</td>
<td valign="top" align="center">7.22 (5.96, 8.63)</td>
<td valign="top" align="center">6.44 (5.45, 7.62)</td>
<td valign="top" align="center">&#x02212;0.11 (&#x02212;0.2, 0)</td>
<td valign="top" align="center">&#x02212;0.32 (&#x02212;0.49&#x02013;0.15)</td>
<td valign="top" align="center">6.32 (5.16, 7.64)</td>
<td valign="top" align="center">4.97 (4.10, 5.94)</td>
<td valign="top" align="center">&#x02212;0.21 (&#x02212;0.32, &#x02212;0.09)</td>
<td valign="top" align="center">&#x02212;0.72 (&#x02212;0.88&#x02013;0.56)</td>
<td valign="top" align="center">8.22 (6.79, 9.95)</td>
<td valign="top" align="center">8.27 (6.97, 9.88)</td>
<td valign="top" align="center">0.01 (&#x02212;0.13, 0.17)</td>
<td valign="top" align="center">0.07 (&#x02212;0.1&#x02013;0.24)</td>
</tr> <tr>
<td valign="top" align="left">Low-middle SDI</td>
<td valign="top" align="center">6.75 (4.99, 8.67)</td>
<td valign="top" align="center">6.24 (4.79, 8.06)</td>
<td valign="top" align="center">&#x02212;0.08 (&#x02212;0.16, 0.02)</td>
<td valign="top" align="center">&#x02212;0.23 (&#x02212;0.46&#x02013;0)</td>
<td valign="top" align="center">6.08 (4.50, 7.80)</td>
<td valign="top" align="center">4.90 (3.68, 6.29)</td>
<td valign="top" align="center">&#x02212;0.19 (&#x02212;0.28, &#x02212;0.10)</td>
<td valign="top" align="center">&#x02212;0.67 (&#x02212;0.9&#x02013;0.44)</td>
<td valign="top" align="center">7.40 (5.37, 9.60)</td>
<td valign="top" align="center">7.75 (5.86, 10.25)</td>
<td valign="top" align="center">0.05 (&#x02212;0.07, 0.21)</td>
<td valign="top" align="center">0.18 (&#x02212;0.06&#x02013;0.42)</td>
</tr>
<tr>
<td valign="top" align="left">Low SDI</td>
<td valign="top" align="center">5.29 (4.03, 6.77)</td>
<td valign="top" align="center">4.79 (3.74, 5.92)</td>
<td valign="top" align="center">&#x02212;0.1 (&#x02212;0.19, 0.03)</td>
<td valign="top" align="center">&#x02212;0.3 (&#x02212;0.61&#x02013;0.01)</td>
<td valign="top" align="center">4.68 (3.47, 5.96)</td>
<td valign="top" align="center">3.78 (2.91, 4.73)</td>
<td valign="top" align="center">0.19 (&#x02212;0.30, &#x02212;0.05)</td>
<td valign="top" align="center">&#x02212;0.71 (&#x02212;1.04&#x02013;0.39)</td>
<td valign="top" align="center">5.90 (4.44, 7.63)</td>
<td valign="top" align="center">5.90 (4.60, 7.40)</td>
<td valign="top" align="center">0.00 (&#x02212;0.16, 0.17)</td>
<td valign="top" align="center">0.07 (&#x02212;0.23&#x02013;0.37)</td>
</tr></tbody>
</table>
<table-wrap-foot>
<p>DALYs, Disability-adjusted life years; ASDR, Age-Standardized Death Rate; ASMR, Age-Standardized Mortality Rate; TPC, Total Percent Change; SDI, Sociodemographic Index.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec>
<title>Gender differences in cardiovascular burden from extreme temperatures</title>
<p>Over the past three decades, men consistently exhibited a higher burden from extreme temperatures than women. For heat-attributable MD, the ASDR increased more rapidly in men (EAPC: 1.47%, 95% CI: 0.97% &#x02212;1.97%) than in women (EAPC: 0.93%, 95% CI: 0.45% &#x02212;1.41%), reaching 2.53 vs. 1.42 per 100,000 in 2021, respectively. A similar pattern was observed for heat-attributable IHD, with ASDR EAPCs of 1.83% (95% CI: 1.48% &#x02212;2.18%) in men and 1.40% (95% CI: 1.04% &#x02212;1.76%) in women, and 2021 ASDRs of 40.34 vs. 21.65 per 100,000.</p>
<p>In contrast, for cold-attributable burden, both sexes showed decreasing trends, but women experienced steeper declines. For MD, the ASDR EAPC was &#x02212;2.38% (95% CI: &#x02212;2.59% to &#x02212;2.16%) in women vs. &#x02212;1.58% (95% CI: &#x02212;1.92% to &#x02212;1.24%) in men; corresponding 2021 ASDRs were 4.47 in women and 9.62 in men. For IHD, EAPCs were &#x02212;1.98% (95% CI: &#x02212;2.10% to &#x02212;1.86%) in women and &#x02212;1.55% (95% CI: &#x02212;1.67% to &#x02212;1.42%) in men, with ASDRs of 84.78 vs. 153.52 per 100,000, respectively (<xref ref-type="fig" rid="F1">Figure 1</xref>).</p>
</sec>
<sec>
<title>Regional differences in cardiovascular burden from extreme temperatures (1990&#x02013;2021)</title>
<p>From 1990 to 2021, the heat-attributable CVD burden increased across most socio-demographic index (SDI) tiers, particularly in low-SDI regions. For MD, high-SDI regions showed a slight decline (ASDR EAPC &#x02212;0.29%), while low-SDI regions experienced significant rises (ASDR EAPC 2.8%). IHD burdens also grew more sharply in lower SDI areas. By 2021, low-middle SDI regions recorded the highest ASDRs for both MD (3.93 per 100,000) and IHD (78.49 per 100,000), contributing 64,292 DALYs for MD and 1,169,778 DALYs for IHD attributable to heat (<xref ref-type="fig" rid="F1">Figure 1</xref>, <xref ref-type="table" rid="T1">Table 1</xref>).</p>
<p>For low temperatures, burdens declined across all SDI tiers, with the steepest reductions in high-SDI regions (MD: ASDR EAPC &#x02212;2.93%; IHD: ASDR EAPC &#x02212;3.66%). Declines were less pronounced in low and low-middle SDI regions. By 2021, middle-high SDI regions had the highest ASDRs for both MD and IHD, contributing &#x0007E;2,833,786 DALYs for IHD and 234,094 DALYs for MD, highlighting persistent cold-related risks even in relatively developed areas. ASMR trends followed similar patterns across SDI levels (<xref ref-type="table" rid="T1">Table 1</xref>).</p>
<p>Significant regional variation were noted. For heat-attributable MD, Eastern Europe saw the largest increase (ASDR TPC 20.01%), and for IHD, Southeast Asia had the largest rise (ASDR TPC 7.59%). For cold-attributable MD, only Central Asia and Eastern Europe exhibited slight increases, while other regions declined. By 2021, Central Asia, South Asia, and North Africa/Middle East bore the highest heat-attributable burdens, while Eastern Europe and Central Asia had the highest cold-attributable ASDRs (<xref ref-type="fig" rid="F2">Figure 2</xref> and <xref ref-type="table" rid="T2">Table 2</xref>).</p>
<table-wrap position="float" id="T2">
<label>Table 2</label>
<caption><p>Comprehensive data on DALYs and mortality rates (ASDR, ASMR), and TPC values for myocardial disease, and ischemic heart disease attributable to high and low temperatures across 21 GBD regions in 1990 vs. 2021.</p></caption>
<table frame="box" rules="all">
<thead>
<tr>
<th valign="top" align="left"><bold>Region</bold></th>
<th valign="top" align="center"><bold>1990 ASDR (95% UI)</bold></th>
<th valign="top" align="center"><bold>2021 ASDR (95% UI)</bold></th>
<th valign="top" align="center"><bold>TPC of ASDR (95% UI)</bold></th>
<th valign="top" align="center"><bold>1990 ASMR (95% UI)</bold></th>
<th valign="top" align="center"><bold>2021 ASMR (95% UI)</bold></th>
<th valign="top" align="center"><bold>TPC of ASMR (95% UI)</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" colspan="7"><bold>Myocardial disease attributable to high temperature</bold></td>
</tr> <tr>
<td valign="top" align="left">Southeast Asia</td>
<td valign="top" align="center">&#x02212;1.20 (&#x02212;1.87, &#x02212;0.59)</td>
<td valign="top" align="center">&#x02212;0.71 (&#x02212;1.25, &#x02212;0.02)</td>
<td valign="top" align="center">&#x02212;1.2 (&#x02212;1.87, &#x02212;0.59)</td>
<td valign="top" align="center">&#x02212;0.05 (&#x02212;0.02, &#x02212;0.08)</td>
<td valign="top" align="center">&#x02212;0.03 (0.01, &#x02212;0.05)</td>
<td valign="top" align="center">&#x02212;0.49 (&#x02212;1.30, &#x02212;0.07)</td>
</tr> <tr>
<td valign="top" align="left">East Asia</td>
<td valign="top" align="center">1.43 (&#x02212;0.01, 3.01)</td>
<td valign="top" align="center">1.25 (&#x02212;0.01, 2.57)</td>
<td valign="top" align="center">1.43 (&#x02212;0.01, 3.01)</td>
<td valign="top" align="center">0.04 (0.09, &#x02212;0.00)</td>
<td valign="top" align="center">0.05 (0.10, &#x02212;0.00)</td>
<td valign="top" align="center">0.22 (&#x02212;0.41, 0.74)</td>
</tr> <tr>
<td valign="top" align="left">Oceania</td>
<td valign="top" align="center">&#x02212;0.72 (&#x02212;1.42, &#x02212;0.39)</td>
<td valign="top" align="center">&#x02212;0.76 (&#x02212;1.36, &#x02212;0.44)</td>
<td valign="top" align="center">&#x02212;0.72 (&#x02212;1.42, &#x02212;0.39)</td>
<td valign="top" align="center">&#x02212;0.02 (&#x02212;0.01, &#x02212;0.05)</td>
<td valign="top" align="center">&#x02212;0.02 (&#x02212;0.01, &#x02212;0.04)</td>
<td valign="top" align="center">&#x02212;0.05 (&#x02212;0.34, 0.36)</td>
</tr> <tr>
<td valign="top" align="left">Central Asia</td>
<td valign="top" align="center">2.42 (0.26, 4.63)</td>
<td valign="top" align="center">6.96 (&#x02212;0.05, 14.92)</td>
<td valign="top" align="center">2.42 (0.26, 4.63)</td>
<td valign="top" align="center">0.07 (0.14, 0.01)</td>
<td valign="top" align="center">0.23 (0.49, &#x02212;0.01)</td>
<td valign="top" align="center">2.12 (&#x02212;0.25, 2.99)</td>
</tr> <tr>
<td valign="top" align="left">Central Europe</td>
<td valign="top" align="center">0.28 (&#x02212;1.09, 1.96)</td>
<td valign="top" align="center">0.90 (&#x02212;1.03, 3.33)</td>
<td valign="top" align="center">2.2 (&#x02212;18.75, 9.08)</td>
<td valign="top" align="center">0.01 (0.10, &#x02212;0.06)</td>
<td valign="top" align="center">0.04 (0.15, &#x02212;0.05)</td>
<td valign="top" align="center">1.77 (&#x02212;14.48, 7.92)</td>
</tr> <tr>
<td valign="top" align="left">Eastern Europe</td>
<td valign="top" align="center">0.10 (&#x02212;0.98, 1.19)</td>
<td valign="top" align="center">2.20 (&#x02212;4.41, 9.38)</td>
<td valign="top" align="center">20.01 (&#x02212;36.74, 87.57)</td>
<td valign="top" align="center">0.00 (0.04, &#x02212;0.03)</td>
<td valign="top" align="center">0.06 (0.25, &#x02212;0.12)</td>
<td valign="top" align="center">15.40 (&#x02212;29.82, 46.80)</td>
</tr> <tr>
<td valign="top" align="left">High-income Asia Pacific</td>
<td valign="top" align="center">1.72 (0.04, 3.71)</td>
<td valign="top" align="center">0.43 (&#x02212;0.07, 0.99)</td>
<td valign="top" align="center">&#x02212;0.75 (&#x02212;0.98, &#x02212;0.69)</td>
<td valign="top" align="center">0.08 (0.17, 0.01)</td>
<td valign="top" align="center">0.02 (0.04, &#x02212;0.00)</td>
<td valign="top" align="center">&#x02212;0.77 (&#x02212;0.93, &#x02212;0.72)</td>
</tr> <tr>
<td valign="top" align="left">Australasia</td>
<td valign="top" align="center">0.74 (&#x02212;0.35, 2.09)</td>
<td valign="top" align="center">0.22 (&#x02212;0.13, 0.65)</td>
<td valign="top" align="center">&#x02212;0.7 (&#x02212;1.02, &#x02212;0.43)</td>
<td valign="top" align="center">0.03 (0.08, &#x02212;0.01)</td>
<td valign="top" align="center">0.01 (0.03, &#x02212;0.01)</td>
<td valign="top" align="center">&#x02212;0.70 (&#x02212;1.01, &#x02212;0.41)</td>
</tr> <tr>
<td valign="top" align="left">Western Europe</td>
<td valign="top" align="center">0.30 (&#x02212;0.27, 1.10)</td>
<td valign="top" align="center">0.21 (&#x02212;0.04, 0.52)</td>
<td valign="top" align="center">&#x02212;0.31 (&#x02212;2.26, 0.87)</td>
<td valign="top" align="center">0.02 (0.06, &#x02212;0.02)</td>
<td valign="top" align="center">0.01 (0.03, &#x02212;0.00)</td>
<td valign="top" align="center">&#x02212;0.41 (&#x02212;2.04, 0.66)</td>
</tr> <tr>
<td valign="top" align="left">Southern Latin America</td>
<td valign="top" align="center">2.42 (&#x02212;0.09, 5.15)</td>
<td valign="top" align="center">1.45 (&#x02212;0.12, 3.08)</td>
<td valign="top" align="center">&#x02212;0.4 (&#x02212;0.56, &#x02212;0.22)</td>
<td valign="top" align="center">0.11 (0.23, &#x02212;0.00)</td>
<td valign="top" align="center">0.07 (0.15, &#x02212;0.01)</td>
<td valign="top" align="center">&#x02212;0.36 (&#x02212;0.53, &#x02212;0.17)</td>
</tr> <tr>
<td valign="top" align="left">High-income North America</td>
<td valign="top" align="center">2.82 (&#x02212;0.77, 7.00)</td>
<td valign="top" align="center">1.90 (&#x02212;0.25, 4.42)</td>
<td valign="top" align="center">&#x02212;0.32 (&#x02212;0.91, 0.04)</td>
<td valign="top" align="center">0.10 (0.25, &#x02212;0.03)</td>
<td valign="top" align="center">0.07 (0.16, &#x02212;0.01)</td>
<td valign="top" align="center">&#x02212;0.32 (&#x02212;0.83, 0.02)</td>
</tr> <tr>
<td valign="top" align="left">Caribbean</td>
<td valign="top" align="center">&#x02212;1.01 (&#x02212;2.01, &#x02212;0.33)</td>
<td valign="top" align="center">&#x02212;0.96 (&#x02212;1.95, &#x02212;0.04)</td>
<td valign="top" align="center">&#x02212;0.05 (&#x02212;0.83, 0.65)</td>
<td valign="top" align="center">&#x02212;0.03 (&#x02212;0.01, &#x02212;0.05)</td>
<td valign="top" align="center">&#x02212;0.02 (0.01, &#x02212;0.05)</td>
<td valign="top" align="center">&#x02212;0.20 (&#x02212;1.40, 0.47)</td>
</tr> <tr>
<td valign="top" align="left">Andean Latin America</td>
<td valign="top" align="center">0.00 (&#x02212;0.15, 0.10)</td>
<td valign="top" align="center">0.06 (&#x02212;0.03, 0.16)</td>
<td valign="top" align="center">12.22 (&#x02212;17.89, 12.38)</td>
<td valign="top" align="center">&#x02212;0.00 (0.00, &#x02212;0.00)</td>
<td valign="top" align="center">0.00 (0.00, &#x02212;0.00)</td>
<td valign="top" align="center">&#x02212;20.41 (&#x02212;12.72, 19.29)</td>
</tr> <tr>
<td valign="top" align="left">Central Latin America</td>
<td valign="top" align="center">&#x02212;0.56 (&#x02212;0.85, &#x02212;0.39)</td>
<td valign="top" align="center">&#x02212;0.01 (&#x02212;0.35, 0.31)</td>
<td valign="top" align="center">&#x02212;0.98 (&#x02212;1.64, &#x02212;0.28)</td>
<td valign="top" align="center">&#x02212;0.02 (&#x02212;0.01, &#x02212;0.03)</td>
<td valign="top" align="center">&#x02212;0.00 (0.01, &#x02212;0.01)</td>
<td valign="top" align="center">&#x02212;0.85 (&#x02212;1.33, &#x02212;0.28)</td>
</tr> <tr>
<td valign="top" align="left">Tropical Latin America</td>
<td valign="top" align="center">&#x02212;0.45 (&#x02212;2.46, 2.15)</td>
<td valign="top" align="center">&#x02212;0.38 (&#x02212;1.20, 0.66)</td>
<td valign="top" align="center">&#x02212;0.16 (&#x02212;2.29, 1.53)</td>
<td valign="top" align="center">&#x02212;0.01 (0.10, &#x02212;0.09)</td>
<td valign="top" align="center">&#x02212;0.01 (0.03, &#x02212;0.04)</td>
<td valign="top" align="center">0.07 (&#x02212;2.12, 1.04)</td>
</tr> <tr>
<td valign="top" align="left">North Africa and Middle East</td>
<td valign="top" align="center">5.52 (&#x02212;0.16, 11.90)</td>
<td valign="top" align="center">5.19 (0.31, 10.53)</td>
<td valign="top" align="center">&#x02212;0.06 (&#x02212;0.43, 0.59)</td>
<td valign="top" align="center">0.16 (0.35, &#x02212;0.00)</td>
<td valign="top" align="center">0.16 (0.33, 0.01)</td>
<td valign="top" align="center">0.01 (&#x02212;0.33, 0.73)</td>
</tr> <tr>
<td valign="top" align="left">South Asia</td>
<td valign="top" align="center">4.29 (&#x02212;1.01, 10.49)</td>
<td valign="top" align="center">5.61 (&#x02212;0.71, 12.39)</td>
<td valign="top" align="center">0.31 (&#x02212;0.48, 1.27)</td>
<td valign="top" align="center">0.15 (0.39, &#x02212;0.03)</td>
<td valign="top" align="center">0.20 (0.46, &#x02212;0.03)</td>
<td valign="top" align="center">0.30 (&#x02212;0.19, 1.19)</td>
</tr> <tr>
<td valign="top" align="left">Central Sub-Saharan Africa</td>
<td valign="top" align="center">&#x02212;2.38 (&#x02212;11.60, 0.16)</td>
<td valign="top" align="center">0.00 (&#x02212;2.84, 2.41)</td>
<td valign="top" align="center">&#x02212;1.0 (&#x02212;10.64, 7.16)</td>
<td valign="top" align="center">&#x02212;0.09 (0.01, &#x02212;0.40)</td>
<td valign="top" align="center">0.00 (0.10, &#x02212;0.11)</td>
<td valign="top" align="center">&#x02212;1.01 (&#x02212;10.05, 8.47)</td>
</tr> <tr>
<td valign="top" align="left">Eastern Sub-Saharan Africa</td>
<td valign="top" align="center">&#x02212;0.23 (&#x02212;1.03, 0.72)</td>
<td valign="top" align="center">0.18 (&#x02212;0.83, 1.39)</td>
<td valign="top" align="center">&#x02212;1.78 (&#x02212;9.14, 12.14)</td>
<td valign="top" align="center">&#x02212;0.01 (0.02, &#x02212;0.03)</td>
<td valign="top" align="center">0.01 (0.04, &#x02212;0.02)</td>
<td valign="top" align="center">&#x02212;2.10 (&#x02212;14.72, 11.49)</td>
</tr> <tr>
<td valign="top" align="left">Southern Sub-Saharan Africa</td>
<td valign="top" align="center">1.35 (&#x02212;0.59, 3.49)</td>
<td valign="top" align="center">1.46 (&#x02212;0.52, 3.72)</td>
<td valign="top" align="center">0.08 (&#x02212;0.22, 0.59)</td>
<td valign="top" align="center">0.06 (0.15, &#x02212;0.03)</td>
<td valign="top" align="center">0.06 (0.15, &#x02212;0.02)</td>
<td valign="top" align="center">0.01 (&#x02212;0.31, 0.50)</td>
</tr> <tr>
<td valign="top" align="left">Western Sub-Saharan Africa</td>
<td valign="top" align="center">&#x02212;1.88 (&#x02212;8.96, 9.20)</td>
<td valign="top" align="center">&#x02212;0.85 (&#x02212;6.25, 7.08)</td>
<td valign="top" align="center">&#x02212;0.55 (&#x02212;4.96, 3.31)</td>
<td valign="top" align="center">&#x02212;0.08 (0.34, &#x02212;0.36)</td>
<td valign="top" align="center">&#x02212;0.03 (0.27, &#x02212;0.24)</td>
<td valign="top" align="center">&#x02212;0.57 (&#x02212;5.56, 2.99)</td>
</tr> <tr>
<td valign="top" align="left" colspan="7"><bold>Ischemic heart disease attributable to high temperature</bold></td>
</tr> <tr>
<td valign="top" align="left">Southeast Asia</td>
<td valign="top" align="center">1.79 (12.10, &#x02212;16.45)</td>
<td valign="top" align="center">15.37 (24.22, 7.73)</td>
<td valign="top" align="center">7.59 (&#x02212;24.80, 14.62)</td>
<td valign="top" align="center">0.09 (0.59, &#x02212;0.69)</td>
<td valign="top" align="center">0.78 (1.26, 0.36)</td>
<td valign="top" align="center">7.29 (&#x02212;27.84, 12.55)</td>
</tr> <tr>
<td valign="top" align="left">East Asia</td>
<td valign="top" align="center">9.34 (35.46, &#x02212;7.01)</td>
<td valign="top" align="center">13.75 (49.90, &#x02212;5.48)</td>
<td valign="top" align="center">0.47 (&#x02212;3.42, 2.73)</td>
<td valign="top" align="center">0.52 (1.96, &#x02212;0.39)</td>
<td valign="top" align="center">0.85 (3.08, &#x02212;0.33)</td>
<td valign="top" align="center">0.63 (&#x02212;3.89, 2.87)</td>
</tr> <tr>
<td valign="top" align="left">Oceania</td>
<td valign="top" align="center">&#x02212;3.82 (&#x02212;0.62, &#x02212;14.97)</td>
<td valign="top" align="center">&#x02212;0.94 (1.09, &#x02212;6.44)</td>
<td valign="top" align="center">&#x02212;0.75 (&#x02212;2.23, &#x02212;0.10)</td>
<td valign="top" align="center">&#x02212;0.17 (&#x02212;0.03, &#x02212;0.64)</td>
<td valign="top" align="center">&#x02212;0.04 (0.05, &#x02212;0.28)</td>
<td valign="top" align="center">&#x02212;0.76 (&#x02212;2.09, &#x02212;0.07)</td>
</tr> <tr>
<td valign="top" align="left">Central Asia</td>
<td valign="top" align="center">38.82 (130.92, &#x02212;1.73)</td>
<td valign="top" align="center">63.34 (178.90, 9.67)</td>
<td valign="top" align="center">0.63 (&#x02212;3.96, 7.47)</td>
<td valign="top" align="center">2.03 (6.88, &#x02212;0.09)</td>
<td valign="top" align="center">3.44 (9.65, 0.51)</td>
<td valign="top" align="center">0.69 (&#x02212;4.07, 7.66)</td>
</tr> <tr>
<td valign="top" align="left">Central Europe</td>
<td valign="top" align="center">8.65 (37.12, &#x02212;2.62)</td>
<td valign="top" align="center">9.40 (36.14, &#x02212;0.72)</td>
<td valign="top" align="center">0.09 (&#x02212;4.58, 5.48)</td>
<td valign="top" align="center">0.46 (2.00, &#x02212;0.14)</td>
<td valign="top" align="center">0.54 (2.06, &#x02212;0.04)</td>
<td valign="top" align="center">0.17 (&#x02212;4.9, 5.66)</td>
</tr> <tr>
<td valign="top" align="left">Eastern Europe</td>
<td valign="top" align="center">5.62 (23.90, &#x02212;1.32)</td>
<td valign="top" align="center">14.08 (52.05, 0.48)</td>
<td valign="top" align="center">1.50 (&#x02212;15.00, 26.14)</td>
<td valign="top" align="center">0.31 (1.33, &#x02212;0.07)</td>
<td valign="top" align="center">0.78 (2.88, 0.03)</td>
<td valign="top" align="center">1.49 (&#x02212;11.86, 20.58)</td>
</tr> <tr>
<td valign="top" align="left">High-income Asia Pacific</td>
<td valign="top" align="center">5.42 (20.55, &#x02212;2.09)</td>
<td valign="top" align="center">2.08 (7.80, &#x02212;0.64)</td>
<td valign="top" align="center">&#x02212;0.62 (&#x02212;0.83, &#x02212;0.46)</td>
<td valign="top" align="center">0.32 (1.20, &#x02212;0.12)</td>
<td valign="top" align="center">0.11 (0.42, &#x02212;0.03)</td>
<td valign="top" align="center">&#x02212;0.65 (&#x02212;0.83, &#x02212;0.53)</td>
</tr> <tr>
<td valign="top" align="left">Australasia</td>
<td valign="top" align="center">4.43 (17.99, &#x02212;2.08)</td>
<td valign="top" align="center">0.63 (3.07, &#x02212;0.88)</td>
<td valign="top" align="center">&#x02212;0.86 (&#x02212;1.93, 0.30)</td>
<td valign="top" align="center">0.25 (1.01, &#x02212;0.11)</td>
<td valign="top" align="center">0.04 (0.19, &#x02212;0.05)</td>
<td valign="top" align="center">&#x02212;0.85 (&#x02212;2.13, 0.25)</td>
</tr> <tr>
<td valign="top" align="left">Western Europe</td>
<td valign="top" align="center">2.73 (12.69, &#x02212;0.86)</td>
<td valign="top" align="center">1.27 (5.66, &#x02212;0.33)</td>
<td valign="top" align="center">&#x02212;0.53 (&#x02212;1.20, 0.58)</td>
<td valign="top" align="center">0.15 (0.71, &#x02212;0.04)</td>
<td valign="top" align="center">0.08 (0.34, &#x02212;0.02)</td>
<td valign="top" align="center">&#x02212;0.5 (&#x02212;1.06, 0.63)</td>
</tr> <tr>
<td valign="top" align="left">Southern Latin America</td>
<td valign="top" align="center">4.22 (17.80, &#x02212;4.12)</td>
<td valign="top" align="center">1.34 (6.68, &#x02212;2.23)</td>
<td valign="top" align="center">&#x02212;0.68 (&#x02212;1.49, 0.98)</td>
<td valign="top" align="center">0.22 (0.95, &#x02212;0.22)</td>
<td valign="top" align="center">0.07 (0.35, &#x02212;0.12)</td>
<td valign="top" align="center">&#x02212;0.69 (&#x02212;1.48, 0.95)</td>
</tr> <tr>
<td valign="top" align="left">High-income North America</td>
<td valign="top" align="center">17.40 (65.05, &#x02212;3.28)</td>
<td valign="top" align="center">9.41 (34.40, &#x02212;2.44)</td>
<td valign="top" align="center">&#x02212;0.46 (&#x02212;1.07, 0.36)</td>
<td valign="top" align="center">0.93 (3.51, &#x02212;0.17)</td>
<td valign="top" align="center">0.50 (1.84, &#x02212;0.13)</td>
<td valign="top" align="center">&#x02212;0.46 (&#x02212;1.12, 0.36)</td>
</tr> <tr>
<td valign="top" align="left">Caribbean</td>
<td valign="top" align="center">&#x02212;0.53 (4.45, &#x02212;11.31)</td>
<td valign="top" align="center">1.31 (4.06, &#x02212;1.69)</td>
<td valign="top" align="center">&#x02212;3.45 (&#x02212;5.94, 4.78)</td>
<td valign="top" align="center">0.02 (0.24, &#x02212;0.46)</td>
<td valign="top" align="center">0.09 (0.22, &#x02212;0.04)</td>
<td valign="top" align="center">3.64 (&#x02212;6.03, 3.23)</td>
</tr> <tr>
<td valign="top" align="left">Andean Latin America</td>
<td valign="top" align="center">&#x02212;1.50 (&#x02212;0.37, &#x02212;3.55)</td>
<td valign="top" align="center">&#x02212;0.02 (1.15, &#x02212;1.12)</td>
<td valign="top" align="center">&#x02212;0.98 (&#x02212;3.24, &#x02212;0.39)</td>
<td valign="top" align="center">&#x02212;0.08 (&#x02212;0.02, &#x02212;0.18)</td>
<td valign="top" align="center">&#x02212;0.00 (0.06, &#x02212;0.06)</td>
<td valign="top" align="center">&#x02212;0.96 (&#x02212;3.04, &#x02212;0.38)</td>
</tr> <tr>
<td valign="top" align="left">Central Latin America</td>
<td valign="top" align="center">&#x02212;3.99 (3.24, &#x02212;13.60)</td>
<td valign="top" align="center">6.98 (14.58, &#x02212;0.19)</td>
<td valign="top" align="center">&#x02212;2.75 (&#x02212;25.08, 17.33)</td>
<td valign="top" align="center">&#x02212;0.21 (0.16, &#x02212;0.70)</td>
<td valign="top" align="center">0.35 (0.73, &#x02212;0.01)</td>
<td valign="top" align="center">&#x02212;2.64 (&#x02212;21.64, 13.9)</td>
</tr> <tr>
<td valign="top" align="left">Tropical Latin America</td>
<td valign="top" align="center">&#x02212;3.87 (8.56, &#x02212;13.95)</td>
<td valign="top" align="center">&#x02212;0.62 (4.98, &#x02212;4.84)</td>
<td valign="top" align="center">&#x02212;0.84 (&#x02212;2.20, 1.30)</td>
<td valign="top" align="center">&#x02212;0.18 (0.42, &#x02212;0.66)</td>
<td valign="top" align="center">&#x02212;0.02 (0.23, &#x02212;0.22)</td>
<td valign="top" align="center">&#x02212;0.86 (&#x02212;2.03, 0.97)</td>
</tr> <tr>
<td valign="top" align="left">North Africa and Middle East</td>
<td valign="top" align="center">103.00 (240.92, 7.94)</td>
<td valign="top" align="center">125.79 (274.00, 23.92)</td>
<td valign="top" align="center">0.22 (0.04, 1.13)</td>
<td valign="top" align="center">4.87 (11.48, 0.33)</td>
<td valign="top" align="center">5.97 (13.07, 1.09)</td>
<td valign="top" align="center">0.23 (0.06, 1.28)</td>
</tr> <tr>
<td valign="top" align="left">South Asia</td>
<td valign="top" align="center">67.51 (124.51, 11.81)</td>
<td valign="top" align="center">89.91 (160.49, 25.58)</td>
<td valign="top" align="center">0.33 (0.12, 1.50)</td>
<td valign="top" align="center">2.91 (5.41, 0.47)</td>
<td valign="top" align="center">3.98 (7.06, 1.16)</td>
<td valign="top" align="center">0.37 (0.16, 1.53)</td>
</tr> <tr>
<td valign="top" align="left">Central Sub-Saharan Africa</td>
<td valign="top" align="center">&#x02212;15.47 (&#x02212;2.39, &#x02212;71.15)</td>
<td valign="top" align="center">&#x02212;5.35 (0.99, &#x02212;18.16)</td>
<td valign="top" align="center">&#x02212;0.65 (&#x02212;1.27, 0.55)</td>
<td valign="top" align="center">&#x02212;0.74 (&#x02212;0.12, &#x02212;3.42)</td>
<td valign="top" align="center">&#x02212;0.26 (0.04, &#x02212;0.90)</td>
<td valign="top" align="center">&#x02212;0.64 (&#x02212;1.22, 0.58)</td>
</tr> <tr>
<td valign="top" align="left">Eastern Sub-Saharan Africa</td>
<td valign="top" align="center">0.33 (5.20, &#x02212;6.17)</td>
<td valign="top" align="center">2.24 (8.99, &#x02212;2.73)</td>
<td valign="top" align="center">5.87 (&#x02212;9.26, 10.08)</td>
<td valign="top" align="center">0.01 (0.23, &#x02212;0.30)</td>
<td valign="top" align="center">0.10 (0.41, &#x02212;0.12)</td>
<td valign="top" align="center">11.06 (&#x02212;12.27, 17.17)</td>
</tr> <tr>
<td valign="top" align="left">Southern Sub-Saharan Africa</td>
<td valign="top" align="center">0.25 (5.18, &#x02212;3.53)</td>
<td valign="top" align="center">0.75 (7.01, &#x02212;4.27)</td>
<td valign="top" align="center">2.04 (&#x02212;3.66, 2.83)</td>
<td valign="top" align="center">0.01 (0.25, &#x02212;0.17)</td>
<td valign="top" align="center">0.04 (0.34, &#x02212;0.21)</td>
<td valign="top" align="center">1.9 (&#x02212;2.76, 2.79)</td>
</tr> <tr>
<td valign="top" align="left">Western Sub-Saharan Africa</td>
<td valign="top" align="center">20.19 (55.24, &#x02212;21.05)</td>
<td valign="top" align="center">36.01 (65.21, 8.49)</td>
<td valign="top" align="center">0.78 (&#x02212;8.20, 11.38)</td>
<td valign="top" align="center">1.01 (2.71, &#x02212;1.02)</td>
<td valign="top" align="center">1.89 (3.42, 0.48)</td>
<td valign="top" align="center">0.87 (&#x02212;8.49, 12.39)</td>
</tr> <tr>
<td valign="top" align="left" colspan="7"><bold>Myocardial disease attributable to low temperature</bold></td>
</tr> <tr>
<td valign="top" align="left">Southeast Asia</td>
<td valign="top" align="center">1.22 (2.14, 0.46)</td>
<td valign="top" align="center">0.75 (1.29, 0.24)</td>
<td valign="top" align="center">&#x02212;0.39 (&#x02212;0.71, &#x02212;0.06)</td>
<td valign="top" align="center">0.06 (0.10, 0.02)</td>
<td valign="top" align="center">0.04 (0.06, 0.01)</td>
<td valign="top" align="center">&#x02212;0.40 (&#x02212;0.68, &#x02212;0.04)</td>
</tr> <tr>
<td valign="top" align="left">East Asia</td>
<td valign="top" align="center">5.19 (7.18, 3.88)</td>
<td valign="top" align="center">2.94 (3.94, 1.53)</td>
<td valign="top" align="center">&#x02212;0.43 (&#x02212;0.69, &#x02212;0.21)</td>
<td valign="top" align="center">0.13 (0.20, 0.10)</td>
<td valign="top" align="center">0.11 (0.15, 0.05)</td>
<td valign="top" align="center">&#x02212;0.19 (&#x02212;0.58, 0.15)</td>
</tr> <tr>
<td valign="top" align="left">Oceania</td>
<td valign="top" align="center">3.13 (4.92, 0.58)</td>
<td valign="top" align="center">2.47 (4.36, &#x02212;0.40)</td>
<td valign="top" align="center">&#x02212;0.21 (&#x02212;0.94, 0.22)</td>
<td valign="top" align="center">0.09 (0.14, 0.02)</td>
<td valign="top" align="center">0.07 (0.12, &#x02212;0.01)</td>
<td valign="top" align="center">&#x02212;0.24 (&#x02212;0.92, 0.21)</td>
</tr> <tr>
<td valign="top" align="left">Central Asia</td>
<td valign="top" align="center">12.13 (15.03, 9.75)</td>
<td valign="top" align="center">27.71 (34.84, 20.94)</td>
<td valign="top" align="center">1.28 (0.80, 1.86)</td>
<td valign="top" align="center">0.39 (0.48, 0.31)</td>
<td valign="top" align="center">0.94 (1.17, 0.73)</td>
<td valign="top" align="center">1.40 (0.91, 2.01)</td>
</tr> <tr>
<td valign="top" align="left">Central Europe</td>
<td valign="top" align="center">32.83 (37.39, 26.94)</td>
<td valign="top" align="center">27.66 (32.33, 21.64)</td>
<td valign="top" align="center">&#x02212;0.16 (&#x02212;0.26, &#x02212;0.03)</td>
<td valign="top" align="center">1.69 (1.92, 1.38)</td>
<td valign="top" align="center">1.27 (1.46, 1.02)</td>
<td valign="top" align="center">&#x02212;0.25 (&#x02212;0.32, &#x02212;0.15)</td>
</tr> <tr>
<td valign="top" align="left">Eastern Europe</td>
<td valign="top" align="center">29.65 (34.61, 21.56)</td>
<td valign="top" align="center">52.94 (65.91, 38.44)</td>
<td valign="top" align="center">0.79 (0.50, 1.16)</td>
<td valign="top" align="center">0.91 (1.06, 0.67)</td>
<td valign="top" align="center">1.48 (1.83, 1.09)</td>
<td valign="top" align="center">0.63 (0.36, 0.99)</td>
</tr> <tr>
<td valign="top" align="left">High-income Asia Pacific</td>
<td valign="top" align="center">10.41 (12.11, 7.56)</td>
<td valign="top" align="center">3.42 (3.94, 2.49)</td>
<td valign="top" align="center">&#x02212;0.67 (&#x02212;0.71, &#x02212;0.64)</td>
<td valign="top" align="center">0.45 (0.53, 0.33)</td>
<td valign="top" align="center">0.14 (0.16, 0.10)</td>
<td valign="top" align="center">&#x02212;0.69 (&#x02212;0.72, &#x02212;0.66)</td>
</tr> <tr>
<td valign="top" align="left">Australasia</td>
<td valign="top" align="center">10.32 (14.18, 0.87)</td>
<td valign="top" align="center">4.21 (5.69, 1.47)</td>
<td valign="top" align="center">&#x02212;0.59 (&#x02212;0.69, &#x02212;0.27)</td>
<td valign="top" align="center">0.38 (0.53, 0.02)</td>
<td valign="top" align="center">0.16 (0.21, 0.05)</td>
<td valign="top" align="center">&#x02212;0.58 (&#x02212;0.69, &#x02212;0.25)</td>
</tr> <tr>
<td valign="top" align="left">Western Europe</td>
<td valign="top" align="center">17.07 (19.87, 13.16)</td>
<td valign="top" align="center">6.21 (7.22, 4.53)</td>
<td valign="top" align="center">&#x02212;0.64 (&#x02212;0.68, &#x02212;0.60)</td>
<td valign="top" align="center">0.91 (1.07, 0.70)</td>
<td valign="top" align="center">0.30 (0.35, 0.22)</td>
<td valign="top" align="center">&#x02212;0.68 (&#x02212;0.71, &#x02212;0.65)</td>
</tr> <tr>
<td valign="top" align="left">Southern Latin America</td>
<td valign="top" align="center">20.68 (28.21, 12.09)</td>
<td valign="top" align="center">9.44 (11.31, 5.98)</td>
<td valign="top" align="center">&#x02212;0.54 (&#x02212;0.64, &#x02212;0.41)</td>
<td valign="top" align="center">0.89 (1.24, 0.52)</td>
<td valign="top" align="center">0.44 (0.52, 0.28)</td>
<td valign="top" align="center">&#x02212;0.51 (&#x02212;0.61, &#x02212;0.37)</td>
</tr> <tr>
<td valign="top" align="left">High-income North America</td>
<td valign="top" align="center">17.79 (21.28, 12.49)</td>
<td valign="top" align="center">8.77 (10.51, 6.52)</td>
<td valign="top" align="center">&#x02212;0.51 (&#x02212;0.55, &#x02212;0.46)</td>
<td valign="top" align="center">0.64 (0.77, 0.45)</td>
<td valign="top" align="center">0.33 (0.39, 0.24)</td>
<td valign="top" align="center">&#x02212;0.48 (&#x02212;0.53, &#x02212;0.42)</td>
</tr> <tr>
<td valign="top" align="left">Caribbean</td>
<td valign="top" align="center">1.85 (2.79, 1.01)</td>
<td valign="top" align="center">1.75 (2.52, 1.06)</td>
<td valign="top" align="center">&#x02212;0.06 (&#x02212;0.24, 0.20)</td>
<td valign="top" align="center">0.06 (0.08, 0.03)</td>
<td valign="top" align="center">0.06 (0.08, 0.04)</td>
<td valign="top" align="center">0.06 (&#x02212;0.12, 0.32)</td>
</tr> <tr>
<td valign="top" align="left">Andean Latin America</td>
<td valign="top" align="center">4.19 (5.30, 2.24)</td>
<td valign="top" align="center">1.84 (2.43, 0.90)</td>
<td valign="top" align="center">&#x02212;0.56 (&#x02212;0.68, &#x02212;0.40)</td>
<td valign="top" align="center">0.12 (0.15, 0.06)</td>
<td valign="top" align="center">0.06 (0.08, 0.03)</td>
<td valign="top" align="center">&#x02212;0.53 (&#x02212;0.66, &#x02212;0.37)</td>
</tr> <tr>
<td valign="top" align="left">Central Latin America</td>
<td valign="top" align="center">1.79 (2.52, 0.89)</td>
<td valign="top" align="center">1.29 (1.87, &#x02212;0.01)</td>
<td valign="top" align="center">&#x02212;0.28 (&#x02212;0.91, 0.04)</td>
<td valign="top" align="center">0.06 (0.08, 0.03)</td>
<td valign="top" align="center">0.04 (0.06, &#x02212;0.00)</td>
<td valign="top" align="center">&#x02212;0.33 (&#x02212;0.95, &#x02212;0.04)</td>
</tr> <tr>
<td valign="top" align="left">Tropical Latin America</td>
<td valign="top" align="center">10.79 (16.50, 5.32)</td>
<td valign="top" align="center">4.77 (7.41, 1.71)</td>
<td valign="top" align="center">&#x02212;0.56 (&#x02212;0.70, &#x02212;0.46)</td>
<td valign="top" align="center">0.44 (0.68, 0.22)</td>
<td valign="top" align="center">0.18 (0.29, 0.06)</td>
<td valign="top" align="center">&#x02212;0.59 (&#x02212;0.73, &#x02212;0.49)</td>
</tr> <tr>
<td valign="top" align="left">North Africa and Middle East</td>
<td valign="top" align="center">8.92 (15.50, 4.46)</td>
<td valign="top" align="center">3.98 (6.66, 2.28)</td>
<td valign="top" align="center">&#x02212;0.55 (&#x02212;0.69, &#x02212;0.35)</td>
<td valign="top" align="center">0.26 (0.45, 0.13)</td>
<td valign="top" align="center">0.14 (0.23, 0.08)</td>
<td valign="top" align="center">&#x02212;0.48 (&#x02212;0.64, &#x02212;0.27)</td>
</tr> <tr>
<td valign="top" align="left">South Asia</td>
<td valign="top" align="center">7.72 (15.41, 1.94)</td>
<td valign="top" align="center">7.57 (13.60, 2.32)</td>
<td valign="top" align="center">&#x02212;0.02 (&#x02212;0.22, 0.44)</td>
<td valign="top" align="center">0.27 (0.56, 0.07)</td>
<td valign="top" align="center">0.28 (0.51, 0.09)</td>
<td valign="top" align="center">0.02 (&#x02212;0.18, 0.53)</td>
</tr> <tr>
<td valign="top" align="left">Central Sub-Saharan Africa</td>
<td valign="top" align="center">6.10 (12.03, 0.30)</td>
<td valign="top" align="center">3.28 (6.55, &#x02212;0.15)</td>
<td valign="top" align="center">&#x02212;0.46 (&#x02212;0.73, 0.08)</td>
<td valign="top" align="center">0.23 (0.47, 0.01)</td>
<td valign="top" align="center">0.13 (0.26, &#x02212;0.01)</td>
<td valign="top" align="center">&#x02212;0.44 (&#x02212;0.73, 0.11)</td>
</tr> <tr>
<td valign="top" align="left">Eastern Sub-Saharan Africa</td>
<td valign="top" align="center">4.13 (6.98, &#x02212;1.85)</td>
<td valign="top" align="center">2.64 (4.31, &#x02212;0.47)</td>
<td valign="top" align="center">&#x02212;0.36 (&#x02212;0.79, 0.10)</td>
<td valign="top" align="center">0.12 (0.20, &#x02212;0.06)</td>
<td valign="top" align="center">0.08 (0.13, &#x02212;0.01)</td>
<td valign="top" align="center">&#x02212;0.33 (&#x02212;0.78, 0.18)</td>
</tr> <tr>
<td valign="top" align="left">Southern Sub-Saharan Africa</td>
<td valign="top" align="center">17.46 (23.97, 9.05)</td>
<td valign="top" align="center">12.82 (17.25, 5.47)</td>
<td valign="top" align="center">&#x02212;0.27 (&#x02212;0.47, &#x02212;0.07)</td>
<td valign="top" align="center">0.78 (1.11, 0.41)</td>
<td valign="top" align="center">0.55 (0.74, 0.24)</td>
<td valign="top" align="center">&#x02212;0.30 (&#x02212;0.51, &#x02212;0.04)</td>
</tr> <tr>
<td valign="top" align="left">Western Sub-Saharan Africa</td>
<td valign="top" align="center">5.53 (11.73, 1.23)</td>
<td valign="top" align="center">1.85 (3.88, 0.38)</td>
<td valign="top" align="center">&#x02212;0.67 (&#x02212;0.78, &#x02212;0.50)</td>
<td valign="top" align="center">0.22 (0.46, 0.05)</td>
<td valign="top" align="center">0.07 (0.15, 0.01)</td>
<td valign="top" align="center">&#x02212;0.68 (&#x02212;0.79, &#x02212;0.52)</td>
</tr> <tr>
<td valign="top" align="left" colspan="7"><bold>Ischemic heart disease attributable to low temperature</bold></td>
</tr> <tr>
<td valign="top" align="left">Southeast Asia</td>
<td valign="top" align="center">36.57 (47.36, 28.07)</td>
<td valign="top" align="center">27.22 (34.00, 21.09)</td>
<td valign="top" align="center">&#x02212;0.26 (&#x02212;0.37, &#x02212;0.10)</td>
<td valign="top" align="center">1.69 (2.19, 1.28)</td>
<td valign="top" align="center">1.34 (1.68, 1.02)</td>
<td valign="top" align="center">&#x02212;0.21 (&#x02212;0.32, &#x02212;0.04)</td>
</tr> <tr>
<td valign="top" align="left">East Asia</td>
<td valign="top" align="center">128.67 (153.61, 106.07)</td>
<td valign="top" align="center">126.70 (155.49, 103.38)</td>
<td valign="top" align="center">&#x02212;0.02 (&#x02212;0.19, 0.22)</td>
<td valign="top" align="center">6.97 (8.30, 5.74)</td>
<td valign="top" align="center">7.73 (9.44, 6.32)</td>
<td valign="top" align="center">0.11 (&#x02212;0.09, 0.36)</td>
</tr> <tr>
<td valign="top" align="left">Oceania</td>
<td valign="top" align="center">113.36 (148.65, 86.71)</td>
<td valign="top" align="center">95.73 (126.55, 71.51)</td>
<td valign="top" align="center">&#x02212;0.16 (&#x02212;0.37, 0.15)</td>
<td valign="top" align="center">4.69 (6.17, 3.70)</td>
<td valign="top" align="center">4.04 (5.32, 3.05)</td>
<td valign="top" align="center">&#x02212;0.14 (&#x02212;0.34, 0.14)</td>
</tr> <tr>
<td valign="top" align="left">Central Asia</td>
<td valign="top" align="center">474.93 (587.27, 417.21)</td>
<td valign="top" align="center">369.53 (457.30, 320.13)</td>
<td valign="top" align="center">&#x02212;0.22 (&#x02212;0.29, &#x02212;0.15)</td>
<td valign="top" align="center">24.80 (30.93, 21.58)</td>
<td valign="top" align="center">20.34 (25.08, 17.53)</td>
<td valign="top" align="center">&#x02212;0.18 (&#x02212;0.25, &#x02212;0.11)</td>
</tr> <tr>
<td valign="top" align="left">Central Europe</td>
<td valign="top" align="center">322.86 (389.68, 282.78)</td>
<td valign="top" align="center">160.96 (202.94, 139.80)</td>
<td valign="top" align="center">&#x02212;0.50 (&#x02212;0.54, &#x02212;0.47)</td>
<td valign="top" align="center">17.24 (20.94, 15.03)</td>
<td valign="top" align="center">9.40 (11.86, 8.10)</td>
<td valign="top" align="center">&#x02212;0.45 (&#x02212;0.49, &#x02212;0.42)</td>
</tr> <tr>
<td valign="top" align="left">Eastern Europe</td>
<td valign="top" align="center">369.56 (447.59, 337.96)</td>
<td valign="top" align="center">303.08 (385.85, 259.67)</td>
<td valign="top" align="center">&#x02212;0.18 (&#x02212;0.27, &#x02212;0.09)</td>
<td valign="top" align="center">20.16 (24.44, 18.07)</td>
<td valign="top" align="center">16.55 (21.11, 14.14)</td>
<td valign="top" align="center">&#x02212;0.18 (&#x02212;0.27, &#x02212;0.09)</td>
</tr> <tr>
<td valign="top" align="left">High-income Asia Pacific</td>
<td valign="top" align="center">85.55 (95.94, 75.86)</td>
<td valign="top" align="center">33.25 (37.41, 28.70)</td>
<td valign="top" align="center">&#x02212;0.61 (&#x02212;0.63, &#x02212;0.59)</td>
<td valign="top" align="center">5.10 (5.74, 4.38)</td>
<td valign="top" align="center">1.83 (2.10, 1.49)</td>
<td valign="top" align="center">&#x02212;0.64 (&#x02212;0.66, &#x02212;0.62)</td>
</tr> <tr>
<td valign="top" align="left">Australasia</td>
<td valign="top" align="center">229.23 (266.92, 207.62)</td>
<td valign="top" align="center">52.79 (61.92, 46.04)</td>
<td valign="top" align="center">&#x02212;0.77 (&#x02212;0.79, &#x02212;0.76)</td>
<td valign="top" align="center">12.73 (14.87, 11.32)</td>
<td valign="top" align="center">3.18 (3.78, 2.69)</td>
<td valign="top" align="center">&#x02212;0.75 (&#x02212;0.77, &#x02212;0.73)</td>
</tr> <tr>
<td valign="top" align="left">Western Europe</td>
<td valign="top" align="center">173.43 (206.66, 153.18)</td>
<td valign="top" align="center">52.42 (61.12, 45.15)</td>
<td valign="top" align="center">&#x02212;0.70 (&#x02212;0.72, &#x02212;0.68)</td>
<td valign="top" align="center">9.56 (11.41, 8.27)</td>
<td valign="top" align="center">3.10 (3.65, 2.57)</td>
<td valign="top" align="center">&#x02212;0.68 (&#x02212;0.7, &#x02212;0.66)</td>
</tr> <tr>
<td valign="top" align="left">Southern Latin America</td>
<td valign="top" align="center">221.26 (249.58, 205.66)</td>
<td valign="top" align="center">74.54 (81.60, 68.16)</td>
<td valign="top" align="center">&#x02212;0.66 (&#x02212;0.69, &#x02212;0.64)</td>
<td valign="top" align="center">11.85 (13.43, 10.78)</td>
<td valign="top" align="center">3.89 (4.28, 3.48)</td>
<td valign="top" align="center">&#x02212;0.67 (&#x02212;0.7, &#x02212;0.65)</td>
</tr> <tr>
<td valign="top" align="left">High-income North America</td>
<td valign="top" align="center">230.18 (279.34, 205.25)</td>
<td valign="top" align="center">95.43 (113.16, 84.48)</td>
<td valign="top" align="center">&#x02212;0.59 (&#x02212;0.60, &#x02212;0.57)</td>
<td valign="top" align="center">12.36 (15.01, 10.65)</td>
<td valign="top" align="center">5.06 (6.04, 4.24)</td>
<td valign="top" align="center">&#x02212;0.59 (&#x02212;0.61, &#x02212;0.57)</td>
</tr> <tr>
<td valign="top" align="left">Caribbean</td>
<td valign="top" align="center">41.03 (51.50, 33.00)</td>
<td valign="top" align="center">23.63 (28.90, 19.16)</td>
<td valign="top" align="center">&#x02212;0.42 (&#x02212;0.51, &#x02212;0.31)</td>
<td valign="top" align="center">2.14 (2.67, 1.73)</td>
<td valign="top" align="center">1.15 (1.41, 0.94)</td>
<td valign="top" align="center">&#x02212;0.46 (&#x02212;0.53, &#x02212;0.37)</td>
</tr> <tr>
<td valign="top" align="left">Andean Latin America</td>
<td valign="top" align="center">91.97 (105.45, 74.41)</td>
<td valign="top" align="center">51.29 (64.45, 40.21)</td>
<td valign="top" align="center">&#x02212;0.44 (&#x02212;0.54, &#x02212;0.31)</td>
<td valign="top" align="center">4.70 (5.35, 3.81)</td>
<td valign="top" align="center">2.70 (3.37, 2.15)</td>
<td valign="top" align="center">&#x02212;0.42 (&#x02212;0.52, &#x02212;0.29)</td>
</tr> <tr>
<td valign="top" align="left">Central Latin America</td>
<td valign="top" align="center">106.57 (122.20, 94.03)</td>
<td valign="top" align="center">82.31 (98.63, 71.58)</td>
<td valign="top" align="center">&#x02212;0.23 (&#x02212;0.32, &#x02212;0.11)</td>
<td valign="top" align="center">5.62 (6.44, 4.95)</td>
<td valign="top" align="center">4.36 (5.22, 3.77)</td>
<td valign="top" align="center">&#x02212;0.22 (&#x02212;0.31, &#x02212;0.1)</td>
</tr> <tr>
<td valign="top" align="left">Tropical Latin America</td>
<td valign="top" align="center">112.87 (135.37, 92.02)</td>
<td valign="top" align="center">50.86 (60.69, 41.78)</td>
<td valign="top" align="center">&#x02212;0.55 (&#x02212;0.57, &#x02212;0.51)</td>
<td valign="top" align="center">5.34 (6.41, 4.28)</td>
<td valign="top" align="center">2.31 (2.77, 1.89)</td>
<td valign="top" align="center">&#x02212;0.57 (&#x02212;0.59, &#x02212;0.53)</td>
</tr> <tr>
<td valign="top" align="left">North Africa and Middle East</td>
<td valign="top" align="center">427.36 (535.84, 347.58)</td>
<td valign="top" align="center">263.22 (331.05, 221.31)</td>
<td valign="top" align="center">&#x02212;0.38 (&#x02212;0.45, &#x02212;0.30)</td>
<td valign="top" align="center">20.81 (26.06, 16.87)</td>
<td valign="top" align="center">13.71 (17.08, 11.52)</td>
<td valign="top" align="center">&#x02212;0.34 (&#x02212;0.4, &#x02212;0.26)</td>
</tr> <tr>
<td valign="top" align="left">South Asia</td>
<td valign="top" align="center">160.64 (212.70, 110.26)</td>
<td valign="top" align="center">157.44 (208.52, 105.90)</td>
<td valign="top" align="center">&#x02212;0.02 (&#x02212;0.14, 0.11)</td>
<td valign="top" align="center">6.86 (9.18, 4.71)</td>
<td valign="top" align="center">6.97 (9.19, 4.66)</td>
<td valign="top" align="center">0.01 (&#x02212;0.11, 0.15)</td>
</tr> <tr>
<td valign="top" align="left">Central Sub-Saharan Africa</td>
<td valign="top" align="center">57.07 (77.66, 40.31)</td>
<td valign="top" align="center">40.15 (52.74, 29.22)</td>
<td valign="top" align="center">&#x02212;0.30 (&#x02212;0.47, &#x02212;0.02)</td>
<td valign="top" align="center">2.77 (3.69, 1.96)</td>
<td valign="top" align="center">2.00 (2.65, 1.46)</td>
<td valign="top" align="center">&#x02212;0.28 (&#x02212;0.45, &#x02212;0.01)</td>
</tr> <tr>
<td valign="top" align="left">Eastern Sub-Saharan Africa</td>
<td valign="top" align="center">67.17 (82.03, 52.65)</td>
<td valign="top" align="center">55.21 (68.16, 44.94)</td>
<td valign="top" align="center">&#x02212;0.18 (&#x02212;0.34, 0.01)</td>
<td valign="top" align="center">3.04 (3.73, 2.41)</td>
<td valign="top" align="center">2.69 (3.29, 2.16)</td>
<td valign="top" align="center">&#x02212;0.12 (&#x02212;0.27, 0.07)</td>
</tr> <tr>
<td valign="top" align="left">Southern Sub-Saharan Africa</td>
<td valign="top" align="center">112.08 (130.59, 92.72)</td>
<td valign="top" align="center">108.45 (123.45, 95.74)</td>
<td valign="top" align="center">&#x02212;0.03 (&#x02212;0.13, 0.11)</td>
<td valign="top" align="center">5.38 (6.31, 4.42)</td>
<td valign="top" align="center">5.53 (6.30, 4.86)</td>
<td valign="top" align="center">0.03 (&#x02212;0.08, 0.19)</td>
</tr> <tr>
<td valign="top" align="left">Western Sub-Saharan Africa</td>
<td valign="top" align="center">32.03 (47.54, 18.52)</td>
<td valign="top" align="center">18.49 (25.92, 11.94)</td>
<td valign="top" align="center">&#x02212;0.42 (&#x02212;0.52, &#x02212;0.27)</td>
<td valign="top" align="center">1.63 (2.40, 0.97)</td>
<td valign="top" align="center">0.97 (1.35, 0.64)</td>
<td valign="top" align="center">&#x02212;0.41 (&#x02212;0.5, &#x02212;0.27)</td>
</tr></tbody>
</table>
<table-wrap-foot>
<p>DALYs, disability-adjusted life years; ASDR, age-standardized death rate; ASMR, age-standardized mortality rate; TPC, total percent change; GBD, global burden of disease.</p>
</table-wrap-foot>
</table-wrap>
<fig position="float" id="F2">
<label>Figure 2</label>
<caption><p>Age-standardized DALYs rate (ASDR) for myocardial disease, and ischemic heart disease attributable to high and low temperatures in 2021, plotted against the sociodemographic index (SDI) for 21 GBD regions. Each dot represents a country, with colors indicating different GBD regions. The dark line was an adaptive association fitted with adaptive Loess regression based on all data points. DALYs, Disability-adjusted life years.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpubh-13-1605624-g0002.tif">
<alt-text>Four scatter plots show the correlation between temperature, attributable disability-adjusted life years (DALY) rates, and socio-demographic index (SDI) across different regions. Top plots focus on myocardial disease; bottom plots on ischemic heart disease. Left side for high temperatures, right side for low temperatures. Each plot includes data points for various world regions, represented by different colors and symbols. Correlation values and significance are provided in each plot. A black line represents trend data across all regions.</alt-text>
</graphic>
</fig>
<p>Temperature-related burdens followed SDI patterns: high-temperature burdens increased in regions with SDI below 0.5, but declined above this threshold. For cold-attributable IHD, burdens increased sharply between SDI 0.6 and 0.75 and then declining at higher SDI levels. For cold-attributable MD, burdens increased below SDI 0.45, fluctuated between 0.45 and 0.75, and declined beyond 0.75 (<xref ref-type="fig" rid="F2">Figure 2</xref>).</p>
</sec>
<sec>
<title>National differences in cardiovascular burden from extreme temperatures</title>
<p>Between 1990 and 2021, heat-attributable cardiovascular trends varied widely by country. MD burden rose in 38% of countries, led by Kazakhstan (total percentage change, TPC = &#x0002B;45.84%), whereas Bangladesh showed the largest decline (&#x02212;104.11%). For IHD, 39% of countries registered increases, headed by Jamaica (&#x0002B;33.78%), with Zambia recording the greatest reduction (&#x02212;44.36%). In 2021, Turkmenistan had the highest heat-attributable MD burden (ASDR 41.22; ASMR 1.22 per 100,000) and Iraq the highest IHD burden (ASDR 467.99; ASMR 24.70 per 100,000; <xref ref-type="fig" rid="F3">Figure 3</xref>; <xref ref-type="supplementary-material" rid="SM1">Supplementary Tables S1</xref>, <xref ref-type="supplementary-material" rid="SM2">S2</xref>).</p>
<fig position="float" id="F3">
<label>Figure 3</label>
<caption><p><bold>(A)</bold> Age-standardized DALY rates (ASDR) and <bold>(B)</bold> total percentage change (TPC) for myocardial disease, as well as ischemic heart disease, attributable to high and low temperatures across countries in 2021. DALYs, Disability-adjusted life years.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpubh-13-1605624-g0003.tif">
<alt-text>Maps display global variations in myocardial and ischemic heart disease risk at high and low temperatures, labeled A and B. Colors indicate risk increases, with regional insets highlighting areas like the Caribbean, Persian Gulf, and Southeast Asia.</alt-text>
</graphic>
</fig>
<p>For cold-attributable burden, most countries improved: only &#x0007E;15% saw increases. Kazakhstan again recorded the largest MD rise (&#x0002B;17.59%), whereas Italy showed the steepest fall (&#x02212;0.87%). In 2021 Kazakhstan also had the highest cold-attributable MD burden (ASDR 75.50; ASMR 2.65 per 100,000). For IHD, Kiribati posted the greatest increase (&#x0002B;7.97%), while the Maldives showed the largest drop (&#x02212;0.88%). Turkmenistan remained highest for cold-attributable IHD (ASDR 556.82; ASMR 29.72 per 100,000). The Cook Islands and Marshall Islands had the lowest burdens for both diseases.</p>
</sec>
<sec>
<title>Age and sex patterns in 2021</title>
<p>Heat-attributable burden: MD ASDR rose steadily with age&#x02014;from 3.93 (60&#x02013;64 years) to 7.40 (80&#x02013;84 years), peaking at 18.26 per 100 000 beyond 95 years; children &#x0003C; 5 year were also vulnerable (3.45). Heat-attributable IHD rose sharply from mid-life, reaching 320.06 per 100,000 beyond 95 years.</p>
<p>Cold-attributable burden: MD ASDR climbed from 16.58 (60&#x02013;64 years) to 35.69 (80&#x02013;84 years) and 124.39 beyond 95 year, with children &#x0003C; 5 year again relatively affected (5.23). Cold-attributable IHD accelerated after 80 years, rising from 340.03 (60&#x02013;64 years) to 1 130.74 (80&#x02013;84 years) and 2 734.64 per 100,000 beyond 95 years (<xref ref-type="fig" rid="F4">Figure 4</xref>; <xref ref-type="supplementary-material" rid="SM3">Supplementary Tables S3</xref>&#x02013;<xref ref-type="supplementary-material" rid="SM10">S10</xref>).</p>
<fig position="float" id="F4">
<label>Figure 4</label>
<caption><p>Global and SDI-stratified distribution of ASDR by 5-year age groups in 2021 for temperature-attributable myocardial and ischemic heart disease: <bold>(A)</bold> myocardial disease&#x02013;high temperatures; <bold>(B)</bold> myocardial disease&#x02013;low temperatures; <bold>(C)</bold> ischemic heart disease&#x02013;high temperatures; <bold>(D)</bold> ischemic heart disease&#x02013;low temperatures. ASDR, age-standardized DALY rate; SDI, Socio-demographic Index.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpubh-13-1605624-g0004.tif">
<alt-text>Four line graphs show age-specific death rates (ASDR) for myocardial and ischemic heart disease across age groups and locations. Panels A and B compare high and low temperatures for myocardial disease, while C and D compare ischemic heart disease. Lines differentiate by location, sex, and Socio-Demographic Index (SDI). Trends indicate variations in ASDRs with higher rates generally in older age groups and differing by temperature and SDI.</alt-text>
</graphic>
</fig>
</sec>
<sec>
<title>Potential risk factors</title>
<p>The three main contributors to the increased global burden of MD and IHD attributable to non-optimal temperatures were aging, population change, and epidemiological progress. For heat-attributable MD, population change contributed 54.79% to the DALY increase, with epidemiological shifts accounting for 27.87% and aging for 17.34%. For heat-attributable IHD, aging accounted for 30.70%, population growth for 33.53%, and epidemiological change for 35.77%. Cold-attributable diseases, aging and population change were the dominant factors, especially in low-SDI regions where population growth was the primary driver (<xref ref-type="fig" rid="F5">Figure 5</xref> and <xref ref-type="supplementary-material" rid="SM11">Supplementary Table S11</xref>).</p>
<fig position="float" id="F5">
<label>Figure 5</label>
<caption><p>Changes in DALYs for myocardial disease, and ischemic heart disease attributable to high and low temperatures, driven by population-level determinants: aging, population growth, and epidemiological change, from 1990 to 2021, globally and across SDI quintiles. The black dot represents the overall change contributed by all three components combined. Positive values indicate an increase in DALYs attributable to the respective component, while negative values indicate a decrease.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpubh-13-1605624-g0005.tif">
<alt-text>Bar charts showing changes in disability-adjusted life years (DALYs) for myocardial and ischemic heart diseases due to high and low temperatures. Categories include global and different SDI levels. Colors indicate contributions from aging (red), population (orange), and epidemiological change (yellow). Black dots mark data points.</alt-text>
</graphic>
</fig>
</sec>
<sec>
<title>Predicted trends</title>
<p>From 2021 to 2040, the global heat-attributable burden of MD and IHD is projected to rise. MD DALYs and mortality are expected to increase steadily, with the global ASDR reaching 2.37 per 100,000 and the ASMR 0.077 per 100,000 (&#x02248;10,117 deaths) by 2040. For IHD, the heat-attributable ASDR is projected to climb to 35.24 per 100,000 and the ASMR to 1.523 per 100,000 (&#x02248;215,318 deaths), peaking around 2034 before a slight decline (<xref ref-type="fig" rid="F6">Figure 6</xref>; <xref ref-type="supplementary-material" rid="SM12">Supplementary Table S12</xref>).</p>
<fig position="float" id="F6">
<label>Figure 6</label>
<caption><p>Temporal trends in ASDR at the global level for temperature-attributable myocardial and ischemic heart disease, with projections to 2040: <bold>(A)</bold> myocardial disease&#x02013;high temperatures; <bold>(B)</bold> myocardial disease&#x02013;low temperatures; <bold>(C)</bold> ischemic heart disease&#x02013;high temperatures; <bold>(D)</bold> ischemic heart disease&#x02013;low temperatures. Solid lines indicate observed rates; dashed lines indicate predicted rates. ASDR, age-standardized DALY rate.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpubh-13-1605624-g0006.tif">
<alt-text>Four line and bar graphs show the number of Disability-Adjusted Life Years (DALYs) from 1990 to 2045 related to temperature impacts on cardiovascular conditions. Graph A shows high temperature and myocardial disease. Graph B depicts low temperature and myocardial disease. Graph C illustrates high temperature with ischemic heart disease, and Graph D shows low temperature with ischemic heart disease. Each graph compares observed and predicted data for global, male, and female groups with orange bars for DALYs and colored lines for age-standardized rates (ASDR) per 100,000 population. A vertical dashed line separates observed and predicted data.</alt-text>
</graphic>
</fig>
<p>For cold-attributable burden, global DALYs and mortality are projected to continue declining. By 2040, the cold-attributable ASDR for MD is expected to fall to 5.56 per 100,000, with an ASMR of 0.217 per 100,000 (&#x02248;29,422 deaths). For IHD, the ASDR is forecast to decrease to 137.18 per 100,000, with an ASMR of 5.193 per 100,000 (&#x02248;756,304 deaths; <xref ref-type="fig" rid="F6">Figure 6</xref>; <xref ref-type="supplementary-material" rid="SM12">Supplementary Table S12</xref>).</p>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<sec>
<title>Global trends and driving factors</title>
<p>Our study confirms that cold temperatures still account for a greater share of global cardiovascular mortality compared to heat. However, while cold-related burdens have steadily decreased, heat-related burdens have continued to rise since 1990. This divergence parallels the accelerating pace of anthropogenic warming and intensified urban heat-island effects highlighted by the IPCC and Lancet Countdown reports (<xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B24">24</xref>). Additionally, incomplete classification and underreporting of heat-related deaths, particularly in regions with inadequate mortality registration systems, may further underestimate the true impact (<xref ref-type="bibr" rid="B10">10</xref>).</p>
</sec>
<sec>
<title>Disease<italic>-</italic>specific observations and mechanisms</title>
<p>Our findings highlight distinct differences between IHD and MD in their susceptibility and mechanisms underlying temperature-related cardiovascular burdens. IHD demonstrates particular vulnerability to high-temperature exposures through mechanisms including increased vascular inflammation, plaque instability, hypercoagulability, and dehydration-induced hemoconcentration, all exacerbating existing atherosclerotic conditions (<xref ref-type="bibr" rid="B25">25</xref>). In contrast, MD&#x02014;encompassing diverse etiologies such as viral myocarditis, autoimmune reactions, and genetic cardiomyopathies&#x02014;is typically exacerbated by heat-induced systemic inflammation, oxidative stress, and direct myocardial injury rather than primarily through vascular or thrombotic pathways (<xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B27">27</xref>). These pathophysiological differences help explain why IHD and MD show distinct epidemiological trends under temperature extremes and emphasize the need for disease-specific prevention and management strategies.</p>
</sec>
<sec>
<title>Mechanisms of age and gender vulnerabilities</title>
<p>The age-related vulnerabilities to extreme temperatures involve specific physiological mechanisms. Children under five exhibit heightened sensitivity due to immature thermoregulatory systems and diagnostic delays (<xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B29">29</xref>). Conversely, older adults face increased risks from impaired vasodilation, reduced sweating capacity, and diminished autonomic control exacerbated by chronic conditions like diabetes and hypertension (<xref ref-type="bibr" rid="B30">30</xref>). Gender disparities across socioeconomic development indices (SDI) showed men consistently having higher burdens, likely due to occupational exposure, lifestyle factors (e.g., smoking, alcohol), and less protective estrogenic vascular effects compared to women (<xref ref-type="bibr" rid="B31">31</xref>&#x02013;<xref ref-type="bibr" rid="B33">33</xref>).</p>
</sec>
<sec>
<title>Spatiotemporal patterns and socioeconomic factors</title>
<p>High-temperature burdens have risen fastest in low-SDI regions, where weak health systems, minimal cooling infrastructure, and widespread outdoor work intensify exposure. Each 1&#x000B0;C rise in temperature is associated with an &#x0007E;9% increase in cardiovascular mortality in lower-middle-income countries compared to high-income settings (<xref ref-type="bibr" rid="B34">34</xref>). While high-SDI regions have largely stabilized or reduced heat- and cold-attributable burdens through better housing, air-conditioning, and heat-alert systems, several upper-middle-SDI economies are now seeing renewed increases, underscoring that economic growth alone does not guarantee resilience (<xref ref-type="bibr" rid="B35">35</xref>, <xref ref-type="bibr" rid="B36">36</xref>).</p>
<p>Against this broader pattern, Eastern Europe has experienced the steepest rise in heat-attributable MD (ASDR &#x0002B;20%), likely driven by high rates of alcohol-related cardiomyopathy (<xref ref-type="bibr" rid="B37">37</xref>), rapid increases in extreme-heat days coupled with low air-conditioning coverage, and population aging combined with high smoking and hypertension prevalence (<xref ref-type="bibr" rid="B38">38</xref>, <xref ref-type="bibr" rid="B39">39</xref>). Southeast Asia records the largest surge in heat-related IHD (ASDR &#x0002B;7.6%), reflecting urban heat islands, limited affordable cooling, and increasing rates of hypertension and diabetes (<xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B40">40</xref>). Although cold-attributable MD has declined globally, Central Asia and Eastern Europe still show slight increases, likely due to poorly insulated housing, low indoor winter temperatures, and persistent high smoking rates (<xref ref-type="bibr" rid="B41">41</xref>). By 2021, heat-related cardiovascular mortality peaks had shifted to Central Asia, South Asia, and North Africa/Middle East, where &#x02265;40&#x000B0;C heatwaves coincide with limited cooling infrastructure, whereas cold-related peaks remained concentrated in Eastern Europe and Central Asia (<xref ref-type="bibr" rid="B42">42</xref>).</p>
<p>Overall, heat-related mortality has been rising while cold-related mortality has decreased. Yet, three exceptional seasons disrupted these trends: the western Russia heatwave in 2010 (<xref ref-type="bibr" rid="B43">43</xref>) and the trans-Eurasian heatwave of 2020 (<xref ref-type="bibr" rid="B44">44</xref>) each triggered significant spikes in cardiovascular deaths, briefly reversing earlier gains from milder summers, heat-action plans, and expanded cooling access. Conversely, the 2005 winter saw an unusual cold-related spike linked to a strong negative Arctic Oscillation (<xref ref-type="bibr" rid="B45">45</xref>, <xref ref-type="bibr" rid="B46">46</xref>), a resurgence of solid-fuel heating, and an influenza B outbreak (<xref ref-type="bibr" rid="B47">47</xref>). These episodes illustrate how single-season extremes can temporarily override long-term trends, and how recent adaptation gains are increasingly challenged by rising heat intensity and an aging global population.</p>
</sec>
<sec>
<title>Comparisons with previous studies</title>
<p>Our findings extend previous work by providing a disease-specific breakdown of temperature-related cardiovascular burdens. Unlike earlier multi-country studies that aggregated all cardiovascular outcomes (<xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B49">49</xref>), our analysis separately quantified IHD and MD burdens across diverse demographics and socioeconomic contexts. Previous GBD analyses primarily considered older populations without detailed sex or regional stratification (<xref ref-type="bibr" rid="B50">50</xref>), whereas our study highlights vulnerabilities across all ages and explicitly quantifies gender-specific risks. Additionally, previous single-country studies noted seasonally increased cardiomyopathy events without comprehensive mortality data (<xref ref-type="bibr" rid="B51">51</xref>, <xref ref-type="bibr" rid="B52">52</xref>); our global perspective fills this gap and underscores sustained heat-related increases in MD. Our future projections, which incorporate updated demographic and epidemiological data, contrast with prior optimistic forecasts based solely on technological adaptation (<xref ref-type="bibr" rid="B53">53</xref>, <xref ref-type="bibr" rid="B54">54</xref>).</p>
</sec>
<sec>
<title>Decomposition analysis insights</title>
<p>Our decomposition analysis revealed that population growth significantly contributed (over 54% for MD and 30% for IHD) to rising heat-related cardiovascular burdens, particularly in rapidly urbanizing lower-SDI regions (<xref ref-type="bibr" rid="B55">55</xref>). Population aging accounted substantially for both MD and IHD burden increases (17.3 and 30.7%, respectively), reflecting age-related physiological vulnerabilities and chronic disease prevalence (<xref ref-type="bibr" rid="B30">30</xref>, <xref ref-type="bibr" rid="B56">56</xref>). Epidemiological transitions, especially increased prevalence of obesity and diabetes, contributed more significantly to IHD (35.8%) compared to MD (27.9%), highlighting IHD&#x00027;s stronger association with modifiable risk factors (<xref ref-type="bibr" rid="B57">57</xref>). The declining cold-related burdens primarily reflect improved housing, heating infrastructure, and healthcare, though aging populations still sustain significant residual risks.</p>
</sec>
<sec>
<title>Strengths and limitations</title>
<p>This study provides the first comprehensive, disease-specific global assessment of temperature-related cardiovascular burdens, incorporating long-term trend analyses and future projections with decomposition of demographic and epidemiological drivers. However, it shares inherent limitations associated with GBD methodologies, including potential misclassification of deaths, incomplete data coverage (particularly in low-SDI settings), and limited assessment of delayed temperature effects or adaptation behaviors. Future research should address these gaps by integrating finer-scale data and evaluating the impacts of adaptation measures more systematically.</p>
</sec>
</sec>
<sec id="s5">
<title>Conclusions and implications</title>
<p>Heat-related IHD represents an increasingly critical global health threat, while MD presents unique vulnerabilities, particularly for young children and older adults. Effective public health interventions must prioritize age-, gender-, and socioeconomic-specific strategies, such as enhancing heat-resilient infrastructure, improving chronic disease management during heatwaves, and targeted interventions addressing occupational and lifestyle risks. Comprehensive, tailored climate-adaptive cardiovascular planning is essential to mitigate growing temperature-related health burdens worldwide.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s6">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s12">Supplementary material</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec sec-type="ethics-statement" id="s7">
<title>Ethics statement</title>
<p>Ethical approval was not required for the study involving humans in accordance with the local legislation and institutional requirements. Written informed consent to participate in this study was not required from the participants or the participants&#x00027; legal guardians/next of kin in accordance with the national legislation and the institutional requirements.</p>
</sec>
<sec sec-type="author-contributions" id="s8">
<title>Author contributions</title>
<p>MG: Visualization, Conceptualization, Investigation, Funding acquisition, Writing &#x02013; original draft. ZL: Data curation, Writing &#x02013; original draft, Methodology. ZX: Methodology, Writing &#x02013; original draft, Data curation. LW: Writing &#x02013; review &#x00026; editing. HX: Writing &#x02013; review &#x00026; editing, Supervision, Project administration. FL: Conceptualization, Project administration, Writing &#x02013; review &#x00026; editing, Investigation, Funding acquisition.</p>
</sec>
<sec sec-type="funding-information" id="s9">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This study was supported by the National Natural Science Foundation of China (No. 82000417); Shandong Provincial Medical and Health Science and Technology Project (No. 202403060982); Joint Science and Technology Program of the Department of Science and Technology, National Administration of Traditional Chinese Medicine (GZY-KJS-SD-2023-091); and Natural Science Foundation of Qingdao (No. 25-1-1-232zyyd-jch).</p>
</sec>
<ack><p>The authors thank the IHME and the Global Burden of Disease study collaborations.</p>
</ack>
<sec sec-type="COI-statement" id="conf1">
<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="s10">
<title>Generative AI statement</title>
<p>The author(s) declare that no Gen AI was used in the creation of this manuscript.</p>
</sec>
<sec sec-type="disclaimer" id="s11">
<title>Publisher&#x00027;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="s12">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fpubh.2025.1605624/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fpubh.2025.1605624/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">
<label>Supplementary Table S1</label>
<caption><p>Comprehensive data on DALYs and mortality rates (ASDR, ASMR), and TPC values for myocardial disease attributable to high and low temperatures across countries in 1990 vs. 2021.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.docx" id="SM2" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>Supplementary Table S2</label>
<caption><p>Comprehensive data on DALYs and mortality rates (ASDR, ASMR), and TPC values for ischemic heart disease attributable to high and low temperatures across countries in 1990 vs. 2021.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.docx" id="SM3" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>Supplementary Table S3</label>
<caption><p>Age-specific DALYs and ASDR for myocardial disease attributable to high temperature, categorized by 5-year age groups, presented globally and by SDI region in 2021.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.docx" id="SM4" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>Supplementary Table S4</label>
<caption><p>Age-specific DALYs and ASDR for myocardial disease attributable to low temperature, categorized by 5-year age groups, presented globally and by SDI region in 2021.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.docx" id="SM5" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>Supplementary Table S5</label>
<caption><p>Age-specific DALYs and ASDR for ischemic heart disease attributable to high temperature, categorized by 5-year age groups, presented globally and by SDI region in 2021.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.docx" id="SM6" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>Supplementary Table S6</label>
<caption><p>Age-specific DALYs and ASDR for ischemic heart disease attributable to low temperature, categorized by 5-year age groups, presented globally and by SDI region in 2021.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.docx" id="SM7" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>Supplementary Table S7</label>
<caption><p>Age-specific death numbers and ASMR for myocardial disease attributable to high temperature, categorized by 5-year age groups, presented globally and by SDI region in 2021.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.docx" id="SM8" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>Supplementary Table S8</label>
<caption><p>Age-specific death numbers and ASMR for myocardial disease attributable to low temperature, categorized by 5-year age groups, presented globally and by SDI region in 2021.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.docx" id="SM9" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>Supplementary Table S9</label>
<caption><p>Age-specific death numbers and ASMR for ischemic heart disease attributable to high temperature, categorized by 5-year age groups, presented globally and by SDI region in 2021.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.docx" id="SM10" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>Supplementary Table S10</label>
<caption><p>Age-specific death numbers and ASMR for ischemic heart disease attributable to low temperature, categorized by 5-year age groups, presented globally and by SDI region in 2021.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.docx" id="SM11" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>Supplementary Table S11</label>
<caption><p>Changes in DALYs and deaths for myocardial disease, and ischemic heart disease attributable to high and low temperatures from 1990 to 2021, categorized globally and by SDI regions.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.docx" id="SM12" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>Supplementary Table S12</label>
<caption><p>Age-standardized DALYs and mortality rates (ASDR, ASMR) for cardiomyopathy, myocarditis, and ischemic heart disease related to high and low temperatures, from 1992 to projected estimates for 2040.</p></caption>
</supplementary-material>
</sec>
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