{"title":"大数据和心血管风险——对肥胖、糖尿病和冠心病的洞察。","authors":"Marcus Dörr","doi":"10.1007/s00059-025-05323-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Cardiovascular diseases (CVD) remain a major global health burden. Obesity and type 2 diabetes mellitus (T2DM) are key modifiable risk factors for coronary heart disease (CHD). The emergence of big data has revolutionized cardiovascular research by enabling deeper risk stratification and detection of complex interactions among clinical, lifestyle, and molecular variables.</p><p><strong>Objective: </strong>This article reviews how big data has advanced our understanding of the links between obesity, T2DM, and CHD. It highlights key findings from large cohort studies and international consortia as well as methodological innovations transforming cardiovascular epidemiology.</p><p><strong>Results: </strong>The data reveal that obesity and diabetes show significant regional differences in prevalence and incidence and are associated with other risk factor such as hypertension. Large-scale cohorts and consortia have confirmed that diabetes substantially increases CVD and mortality risk two- to fourfold and is linked to an up to 75% higher mortality rate, with earlier onset and poor glycemic control worsening outcomes. Novel approaches, including polygenic risk scores, machine learning, and real-world data integration, have improved prediction and causal inference. The interplay between obesity and diabetes is a major driver of CHD burden.</p><p><strong>Conclusion: </strong>Big data has enhanced our understanding of cardiovascular risks associated with obesity and diabetes, improved risk prediction models, and provided a foundation for precision prevention strategies. Continued investment in large cohorts, data harmonization, and digital health tools is essential in order to translate these insights into effective public health strategies and reduce the global CVD burden.</p>","PeriodicalId":12863,"journal":{"name":"Herz","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Big data and cardiovascular risk-insights into obesity, diabetes, and coronary heart disease.\",\"authors\":\"Marcus Dörr\",\"doi\":\"10.1007/s00059-025-05323-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Cardiovascular diseases (CVD) remain a major global health burden. Obesity and type 2 diabetes mellitus (T2DM) are key modifiable risk factors for coronary heart disease (CHD). The emergence of big data has revolutionized cardiovascular research by enabling deeper risk stratification and detection of complex interactions among clinical, lifestyle, and molecular variables.</p><p><strong>Objective: </strong>This article reviews how big data has advanced our understanding of the links between obesity, T2DM, and CHD. It highlights key findings from large cohort studies and international consortia as well as methodological innovations transforming cardiovascular epidemiology.</p><p><strong>Results: </strong>The data reveal that obesity and diabetes show significant regional differences in prevalence and incidence and are associated with other risk factor such as hypertension. Large-scale cohorts and consortia have confirmed that diabetes substantially increases CVD and mortality risk two- to fourfold and is linked to an up to 75% higher mortality rate, with earlier onset and poor glycemic control worsening outcomes. Novel approaches, including polygenic risk scores, machine learning, and real-world data integration, have improved prediction and causal inference. The interplay between obesity and diabetes is a major driver of CHD burden.</p><p><strong>Conclusion: </strong>Big data has enhanced our understanding of cardiovascular risks associated with obesity and diabetes, improved risk prediction models, and provided a foundation for precision prevention strategies. Continued investment in large cohorts, data harmonization, and digital health tools is essential in order to translate these insights into effective public health strategies and reduce the global CVD burden.</p>\",\"PeriodicalId\":12863,\"journal\":{\"name\":\"Herz\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2025-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Herz\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00059-025-05323-z\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Herz","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00059-025-05323-z","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Big data and cardiovascular risk-insights into obesity, diabetes, and coronary heart disease.
Background: Cardiovascular diseases (CVD) remain a major global health burden. Obesity and type 2 diabetes mellitus (T2DM) are key modifiable risk factors for coronary heart disease (CHD). The emergence of big data has revolutionized cardiovascular research by enabling deeper risk stratification and detection of complex interactions among clinical, lifestyle, and molecular variables.
Objective: This article reviews how big data has advanced our understanding of the links between obesity, T2DM, and CHD. It highlights key findings from large cohort studies and international consortia as well as methodological innovations transforming cardiovascular epidemiology.
Results: The data reveal that obesity and diabetes show significant regional differences in prevalence and incidence and are associated with other risk factor such as hypertension. Large-scale cohorts and consortia have confirmed that diabetes substantially increases CVD and mortality risk two- to fourfold and is linked to an up to 75% higher mortality rate, with earlier onset and poor glycemic control worsening outcomes. Novel approaches, including polygenic risk scores, machine learning, and real-world data integration, have improved prediction and causal inference. The interplay between obesity and diabetes is a major driver of CHD burden.
Conclusion: Big data has enhanced our understanding of cardiovascular risks associated with obesity and diabetes, improved risk prediction models, and provided a foundation for precision prevention strategies. Continued investment in large cohorts, data harmonization, and digital health tools is essential in order to translate these insights into effective public health strategies and reduce the global CVD burden.
期刊介绍:
Herz is the high-level journal for further education for all physicians interested in cardiology. The individual issues of the journal each deal with specific topics and comprise review articles in English and German written by competent and esteemed authors. They provide up-to-date and comprehensive information concerning the speciality dealt with in the issue. Due to the fact that all relevant aspects of the pertinent topic of an issue are considered, an overview of the current status and progress in cardiology is presented. Reviews and original articles round off the spectrum of information provided.