Tiange Wang1, Jieli Lu1, Qing Su2, Yuhong Chen1, Yufang Bi1, Yiming Mu3, Lulu Chen4, Ruying Hu5, Xulei Tang6, Xuefeng Yu7, Mian Li1, Min Xu1, Yu Xu1, Zhiyun Zhao1, Li Yan8, Guijun Qin9, Qin Wan10, Gang Chen11, Meng Dai1, Di Zhang1, Zhengnan Gao12, Guixia Wang13, Feixia Shen14, Zuojie Luo15, Yingfen Qin15, Li Chen16, Yanan Huo17, Qiang Li18, Zhen Ye5, Yinfei Zhang19, Chao Liu20, Youmin Wang21, Shengli Wu22, Tao Yang23, Huacong Deng24, Donghui Li25, Shenghan Lai26, Zachary T Bloomgarden27, Lixin Shi28, Guang Ning1, Jiajun Zhao29, Weiqing Wang1. 1. Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China. 2. Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China. 3. Chinese People's Liberation Army General Hospital, Beijing, China. 4. Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 5. Zhejiang Provincial Center for Disease Control and Prevention, Zhejiang, China. 6. The First Hospital of Lanzhou University, Lanzhou, China. 7. Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 8. Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China. 9. The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China. 10. The Affiliated Hospital of Luzhou Medical College, Luzhou, China. 11. Fujian Provincial Hospital, Fujian Medical University, Fuzhou, China. 12. Dalian Municipal Central Hospital, Dalian, Chin. 13. The First Hospital of Jilin University, Changchun, China. 14. The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. 15. The First Affiliated Hospital of Guangxi Medical University, Nanning, China. 16. Qilu Hospital of Shandong University, Jinan, China. 17. Jiangxi Provincial People's Hospital Affiliated to Nanchang University, Nanchang, China. 18. The Second Affiliated Hospital of Harbin Medical University, Harbin, China. 19. Central Hospital of Shanghai Jiading District, Shanghai, China. 20. Jiangsu Province Hospital on Integration of Chinese and Western Medicine, Nanjing, China. 21. The First Affiliated Hospital of Anhui Medical University, Hefei, China. 22. Karamay Municipal People's Hospital, Xinjiang, China. 23. The First Affiliated Hospital of Nanjing Medical University, Nanjing, China. 24. The First Affiliated Hospital of Chongqing Medical University, Chongqing, China. 25. Department of Gastrointestinal Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, Texas. 26. Johns Hopkins University School of Medicine, Baltimore, Maryland. 27. Icahn School of Medicine at Mount Sinai, New York, New York. 28. Affiliated Hospital of Guiyang Medical College, Guiyang, China. 29. Shandong Provincial Hospital affiliated to Shandong University, Jinan, China.
Abstract
Importance: Whether optimal cardiovascular health metrics may counteract the risk of cardiovascular events among patients with prediabetes or diabetes is unclear. Objective: To investigate the associations of ideal cardiovascular health metrics (ICVHMs) with subsequent development of cardiovascular disease (CVD) among participants with prediabetes or diabetes as compared with participants with normal glucose regulation. Design, Setting, and Participants: The China Cardiometabolic Disease and Cancer Cohort Study was a nationwide, population-based, prospective cohort study of 20 communities from various geographic regions in China. The study included 111 765 participants who were free from CVD or cancer at baseline. Data were analyzed between 2011 and 2016. Exposures: Prediabetes and diabetes were defined according to the American Diabetes Association 2010 criteria. Seven ICVHMs were adapted from the American Heart Association recommendations. Main Outcomes and Measures: The composite of incident fatal or nonfatal CVD, including cardiovascular death, myocardial infarction, stroke, and hospitalized or treated heart failure. Results: Of the 111 765 participants, 24 881 (22.3%) had normal glucose regulation, 61 024 (54.6%) had prediabetes, and 25 860 (23.1%) had diabetes. Mean (SD) age ranged from 52.9 (8.6) years to 59.4 (8.7) years. Compared with participants with normal glucose regulation, among participants with prediabetes, the multivariable-adjusted hazard ratio for CVD was 1.34 (95% CI, 1.16-1.55) for participants who had 1 ICVHM or less and 0.57 (95% CI, 0.43-0.75) for participants who had at least 5 ICVHMs; among participants with diabetes, the hazard ratios for CVD were 2.05 (95% CI, 1.76-2.38) and 0.80 (95% CI, 0.56-1.15) for participants who had 1 ICVHM or less and at least 5 ICVHMs, respectively. Such pattern of association between ICVHMs and CVD was more prominent for participants younger than 55 years (prediabetes and at least 5 ICVHMs: hazard ratio [HR], 0.32; 95% CI, 0.16-0.63; 1 ICVHM or less: HR, 1.58; 95% CI, 1.13-2.21; diabetes and at least 5 ICVHMs: HR, 0.99; 95% CI, 0.44-2.26; 1 ICVHM or less: HR, 2.46; 95% CI, 1.71-3.54; compared with normal glucose regulation) than for participants 65 years or older (prediabetes and at least 5 ICVHMs: HR, 0.80; 95% CI, 0.50-1.26; 1 ICVHM or less: HR, 1.01; 95% CI, 0.79-1.31; diabetes and at least 5 ICVHMs: HR, 0.79; 95% CI, 0.46-1.35; 1 ICVHM or less: HR, 1.73; 95% CI, 1.36-2.22, compared with normal glucose regulation; P values for interaction ≤.02). Additionally, the hazard ratio for CVD per additional ICVHM was 0.82 (95% CI, 0.79-0.86) among participants with prediabetes and was 0.85 (95% CI, 0.80-0.89) among participants with diabetes. Conclusions and Relevance: Participants with prediabetes or diabetes who had 5 or more ICVHMs exhibited lower or no significant excess CVD risks compared with the participants with normal glucose regulation.
Importance: Whether optimal cardiovascular health metrics may counteract the risk of cardiovascular events among patients with prediabetes or diabetes is unclear. Objective: To investigate the associations of ideal cardiovascular health metrics (ICVHMs) with subsequent development of cardiovascular disease (CVD) among participants with prediabetes or diabetes as compared with participants with normal glucose regulation. Design, Setting, and Participants: The China Cardiometabolic Disease and Cancer Cohort Study was a nationwide, population-based, prospective cohort study of 20 communities from various geographic regions in China. The study included 111 765 participants who were free from CVD or cancer at baseline. Data were analyzed between 2011 and 2016. Exposures: Prediabetes and diabetes were defined according to the American Diabetes Association 2010 criteria. Seven ICVHMs were adapted from the American Heart Association recommendations. Main Outcomes and Measures: The composite of incident fatal or nonfatal CVD, including cardiovascular death, myocardial infarction, stroke, and hospitalized or treated heart failure. Results: Of the 111 765 participants, 24 881 (22.3%) had normal glucose regulation, 61 024 (54.6%) had prediabetes, and 25 860 (23.1%) had diabetes. Mean (SD) age ranged from 52.9 (8.6) years to 59.4 (8.7) years. Compared with participants with normal glucose regulation, among participants with prediabetes, the multivariable-adjusted hazard ratio for CVD was 1.34 (95% CI, 1.16-1.55) for participants who had 1 ICVHM or less and 0.57 (95% CI, 0.43-0.75) for participants who had at least 5 ICVHMs; among participants with diabetes, the hazard ratios for CVD were 2.05 (95% CI, 1.76-2.38) and 0.80 (95% CI, 0.56-1.15) for participants who had 1 ICVHM or less and at least 5 ICVHMs, respectively. Such pattern of association between ICVHMs and CVD was more prominent for participants younger than 55 years (prediabetes and at least 5 ICVHMs: hazard ratio [HR], 0.32; 95% CI, 0.16-0.63; 1 ICVHM or less: HR, 1.58; 95% CI, 1.13-2.21; diabetes and at least 5 ICVHMs: HR, 0.99; 95% CI, 0.44-2.26; 1 ICVHM or less: HR, 2.46; 95% CI, 1.71-3.54; compared with normal glucose regulation) than for participants 65 years or older (prediabetes and at least 5 ICVHMs: HR, 0.80; 95% CI, 0.50-1.26; 1 ICVHM or less: HR, 1.01; 95% CI, 0.79-1.31; diabetes and at least 5 ICVHMs: HR, 0.79; 95% CI, 0.46-1.35; 1 ICVHM or less: HR, 1.73; 95% CI, 1.36-2.22, compared with normal glucose regulation; P values for interaction ≤.02). Additionally, the hazard ratio for CVD per additional ICVHM was 0.82 (95% CI, 0.79-0.86) among participants with prediabetes and was 0.85 (95% CI, 0.80-0.89) among participants with diabetes. Conclusions and Relevance: Participants with prediabetes or diabetes who had 5 or more ICVHMs exhibited lower or no significant excess CVD risks compared with the participants with normal glucose regulation.
Authors: Aaron R Folsom; Hiroshi Yatsuya; Jennifer A Nettleton; Pamela L Lutsey; Mary Cushman; Wayne D Rosamond Journal: J Am Coll Cardiol Date: 2011-04-19 Impact factor: 24.094
Authors: Donald M Lloyd-Jones; Yuling Hong; Darwin Labarthe; Dariush Mozaffarian; Lawrence J Appel; Linda Van Horn; Kurt Greenlund; Stephen Daniels; Graham Nichol; Gordon F Tomaselli; Donna K Arnett; Gregg C Fonarow; P Michael Ho; Michael S Lauer; Frederick A Masoudi; Rose Marie Robertson; Véronique Roger; Lee H Schwamm; Paul Sorlie; Clyde W Yancy; Wayne D Rosamond Journal: Circulation Date: 2010-01-20 Impact factor: 29.690
Authors: Alexander Thompson; Emanuele Di Angelantonio; Pei Gao; Nadeem Sarwar; Sreenivasa Rao Kondapally Seshasai; Stephen Kaptoge; Peter H Whincup; Kenneth J Mukamal; Richard F Gillum; Ingar Holme; Inger Njølstad; Astrid Fletcher; Peter Nilsson; Sarah Lewington; Rory Collins; Vilmundur Gudnason; Simon G Thompson; Naveed Sattar; Elizabeth Selvin; Frank B Hu; John Danesh Journal: N Engl J Med Date: 2011-03-03 Impact factor: 91.245
Authors: William C Hsu; Maria Rosario G Araneta; Alka M Kanaya; Jane L Chiang; Wilfred Fujimoto Journal: Diabetes Care Date: 2015-01 Impact factor: 19.112
Authors: Gráinne H Long; Andrew J M Cooper; Nicholas J Wareham; Simon J Griffin; Rebecca K Simmons Journal: Diabetes Care Date: 2014-03-21 Impact factor: 19.112
Authors: Natalia Drobek; Paweł Sowa; Piotr Jankowski; Maciej Haberka; Zbigniew Gąsior; Dariusz Kosior; Danuta Czarnecka; Andrzej Pająk; Karolina Szostak-Janiak; Agnieszka Krzykwa; Małgorzata Setny; Paweł Kozieł; Marlena Paniczko; Jacek Jamiołkowski; Irina Kowalska; Karol Kamiński Journal: J Clin Med Date: 2021-05-05 Impact factor: 4.241
Authors: Jie Shi; Xiaoyong Li; Weiwei Zhang; Yixin Niu; Ning Lin; Hongmei Zhang; Guang Ning; Jiangao Fan; Li Qin; Qing Su; Zhen Yang Journal: Front Cardiovasc Med Date: 2021-05-10