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        <identifier>oai:figshare.com:article/34032057</identifier>
        <datestamp>2026-09-30T11:52:42Z</datestamp>
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          <dc:title>Supplementary file 1_Environmental cold exposure and cardiovascular mortality: biological mechanisms, regional heterogeneity, and public health implications.docx</dc:title>
          <dc:creator>Ling-Jie Xiao (25143687)</dc:creator>
          <dc:creator>Xin-Yu Ma (20748425)</dc:creator>
          <dc:creator>Ji-Zu Shi (25143690)</dc:creator>
          <dc:subject>Public Health and Health Services not elsewhere classified</dc:subject>
          <dc:subject>cardiovascular mortality</dc:subject>
          <dc:subject>climate adaptation</dc:subject>
          <dc:subject>cold exposure</dc:subject>
          <dc:subject>environmental health</dc:subject>
          <dc:subject>regional heterogeneity</dc:subject>
          <dc:subject>social determinants of health</dc:subject>
          <dc:description>Background&lt;p&gt;Ambient cold exposure has been associated with increased cardiovascular mortality worldwide, but effects vary across climatic and socioeconomic settings. This narrative review synthesizes epidemiological evidence on geographic variation in cold-related cardiovascular mortality and considers environmental, biological, and societal factors that may contribute to the observed patterns.&lt;/p&gt;Methods&lt;p&gt;We conducted a narrative review of epidemiological studies investigating associations between ambient cold exposure and cardiovascular mortality. Climatic setting and socioeconomic context were considered as separate analytical dimensions, using local temperature distributions, seasonal patterns, study-specific cold definitions, income classification, housing and heating conditions, healthcare accessibility, and other contextual characteristics where relevant. Because study designs, exposure definitions, lag structures, outcomes, and effect measures were heterogeneous, the synthesis was qualitative; no formal quantitative pooling, causal attribution, or direct ranking of regional vulnerability was undertaken.&lt;/p&gt;Results&lt;p&gt;Evidence suggests that cold-related cardiovascular mortality varies across climatic and socioeconomic settings. Among 26 epidemiological studies contributing to the regional synthesis, substantial heterogeneity was observed in study design, population coverage, temperature metrics, cold definitions, lag structures, covariate adjustment, analytical approaches, outcomes, and effect measures. Methodological credibility was considered qualitatively rather than through a formal risk-of-bias score, with greater interpretive weight given to large multi-location, nationwide, or within-country studies applying standardized or internally consistent analytical frameworks. Illustrative reported estimates included approximately 6.3% of cardiovascular deaths attributable to temperatures below the county-specific minimum mortality temperature in a US analysis, 11.4% (95% CI 6.0–15.4%; lag 0–14 days) attributable to temperatures below the city-specific optimum temperature in a seven-city Norwegian analysis, and a cold-wave-related cardiovascular mortality RR of 1.076 (95% CI 1.061–1.090; lag 0–3 days) in a nationwide Thai study. Because exposure definitions, lag structures, analytical approaches, outcomes, and effect measures differed substantially among studies, no consistent quantitative gradient in vulnerability by climatic setting, latitude, or socioeconomic context could be established. The qualitative evidence suggests that regional patterns may reflect a combination of climatic conditions, biological susceptibility, behavioral responses, socioeconomic circumstances, housing and heating conditions, healthcare capacity, population-level adaptive capacity, and methodological differences. Their relative contributions cannot be determined from the available evidence, and evidence from many warm-climate and lower-resource settings remains limited.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-30T11:52:42Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.3389/fpubh.2026.1961371.s001</dc:identifier>
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          <dc:rights>CC BY 4.0</dc:rights>
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