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Li Z, Liu M, Chen B, Wu Y, Jia H, Geng R, Wang Y, Zhang X, Yang Y, Cui J, Lu J, Guo Z, Li X, Zhang W. Association of high-normal blood pressure defined by the 2023 European Society of Hypertension guideline with mortality in the Chinese population: a nationwide, population-based, prospective study of 3.6 million adults. BMC Med 2025; 23:226. [PMID: 40241124 PMCID: PMC12004562 DOI: 10.1186/s12916-025-04055-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2024] [Accepted: 04/08/2025] [Indexed: 04/18/2025] Open
Abstract
BACKGROUND The relationship between high-normal blood pressure (BP) and mortality lacks high-quality evidence based on large population cohorts. This study aims to comprehensively investigate the association of high-normal BP and its trajectory with all-cause and cause-specific mortality. METHODS In this community-based population cohort from the China Health Evaluation And risk Reduction Through nationwide teamwork (ChinaHEART) project, 3,598,940 participants aged 35-75 years with data for baseline BP were included. High-normal BP was defined as a systolic BP (SBP) of 130-139 mmHg and/or a diastolic BP (DBP) of 85-89 mmHg at baseline. Overall, 78,130 participants with three or more BP measurements were included in the trajectory pattern analysis during the follow-up. Four BP change trajectory patterns were identified. RESULTS For the baseline BP analysis, compared with the optimal BP group (SBP < 120 mmHg and DBP < 80 mmHg [18.1%]), participants with high-normal BP (18.7%) had an increase of 4% in all-cause mortality risk (hazard ratio [HR] 1.04, 95% confidence interval [CI] 1.01-1.07) and an increase of 28% in cardiovascular disease (CVD) mortality risk (HR 1.28, 95% CI 1.21-1.34), with the greatest increase in mortality risk observed for hemorrhagic stroke (HR 1.75, 95% CI 1.55-1.98). Among the BP trajectory patterns, compared with participants with optimal-stable BP, those with high-normal-increasing BP had an increase of 35% in all-cause mortality risk (HR 1.35, 95% CI 1.07-1.70) and an increase in CVD mortality risk of 57% (HR 1.57, 95% CI 1.11-2.24), with the greatest increase in mortality risk also observed for hemorrhagic stroke (HR 3.75, 95% CI 1.50-9.34). Approximately 0.7% and 1.6% of all-cause mortality was attributable to high-normal BP at baseline and the high-normal-increasing BP trajectory pattern, respectively. CONCLUSIONS Individuals with high-normal BP at baseline exhibited a significantly elevated mortality risk and especially for risk of hemorrhagic stroke mortality during the follow-up. This positive association may be mainly attributed to the "high-normal-increasing" BP change over time.
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Affiliation(s)
- Zhiwei Li
- National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Beijing, 100037, People's Republic of China
| | - Mengmeng Liu
- Central China Subcenter of National Center for Cardiovascular Diseases, Henan Cardiovascular Disease Center, Fuwai Central-China Cardiovascular Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, 450000, People's Republic of China
| | - Bowang Chen
- National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Beijing, 100037, People's Republic of China
| | - Yuelin Wu
- National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Beijing, 100037, People's Republic of China
| | - Hui Jia
- Central China Subcenter of National Center for Cardiovascular Diseases, Henan Cardiovascular Disease Center, Fuwai Central-China Cardiovascular Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, 450000, People's Republic of China
| | - Ruirui Geng
- Central China Subcenter of National Center for Cardiovascular Diseases, Henan Cardiovascular Disease Center, Fuwai Central-China Cardiovascular Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, 450000, People's Republic of China
| | - Yixiao Wang
- National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Beijing, 100037, People's Republic of China
| | - Xiaoyan Zhang
- National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Beijing, 100037, People's Republic of China
| | - Yang Yang
- National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Beijing, 100037, People's Republic of China
| | - Jianlan Cui
- National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Beijing, 100037, People's Republic of China
| | - Jiapeng Lu
- National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Beijing, 100037, People's Republic of China
| | - Zhiping Guo
- Central China Subcenter of National Center for Cardiovascular Diseases, Henan Cardiovascular Disease Center, Fuwai Central-China Cardiovascular Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, 450000, People's Republic of China.
- Henan Key Laboratory of Chronic Disease, Fuwai Central China Cardiovascular Hospital, Zhengzhou, 450000, People's Republic of China.
| | - Xi Li
- National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Beijing, 100037, People's Republic of China.
- Central China Subcenter of National Center for Cardiovascular Diseases, Henan Cardiovascular Disease Center, Fuwai Central-China Cardiovascular Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, 450000, People's Republic of China.
- Shenzhen Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Shenzhen, 518000, People's Republic of China.
| | - Weili Zhang
- National Clinical Research Center of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Beijing, 100037, People's Republic of China.
- Central China Subcenter of National Center for Cardiovascular Diseases, Henan Cardiovascular Disease Center, Fuwai Central-China Cardiovascular Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, 450000, People's Republic of China.
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Sun Z, Zhang H, Ding Y, Yu C, Sun D, Pang Y, Pei P, Yang L, Chen Y, Du H, Hu W, Avery D, Chen J, Chen Z, Li L, Lv J. Cost-Effectiveness of Salt Substitution and Antihypertensive Drug Treatment in Chinese Prehypertensive Adults. Hypertension 2024; 81:2529-2539. [PMID: 39465247 DOI: 10.1161/hypertensionaha.124.23412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Accepted: 10/09/2024] [Indexed: 10/29/2024]
Abstract
BACKGROUND Recent guidelines recommend antihypertensive drug treatment for prehypertensive individuals with blood pressure between 130/80 and 139/89 mm Hg. This study evaluates the cost-effectiveness of 3 interventions in Chinese prehypertensive adults: salt substitution, antihypertensive drug treatment, and their combination. METHODS We developed a Markov cohort model to estimate cardiovascular disease (CVD) events, costs, and quality-adjusted life years (QALYs) over a lifetime. Data from the China Kadoorie Biobank informed the simulation. Costs and utilities were drawn from published sources. We evaluated the cost-effectiveness of salt substitution alone, antihypertensive drug treatment alone, and a combination of the 2, focusing on the overall prehypertensive population, those at high CVD risk, and different starting ages (40, 50, 60, and 70 years). Incremental cost-effectiveness ratios (ICERs) were calculated per QALY gained. RESULTS Salt substitution at age 40 years is the only cost-effective strategy for prehypertensive individuals, with an ICER of $6413.62/QALY. For those at high CVD risk, the combination intervention starting at age 40 years is most cost-effective, with an ICER of $2913.30/QALY. Interventions initiated at younger ages yielded greater CVD reductions and lower ICERs. For example, a combined intervention at age 40 years reduces CVD events by 5.3% with an ICER of $2913.30/QALY, compared with 4.9% and $32 635.33/QALY at age 70 years. These results were consistent across sensitivity analyses. CONCLUSIONS In China, replacing usual salt with a salt substitute is more cost-effective than treating prehypertensive individuals over the age of 40 years with antihypertensive drugs. Furthermore, starting intervention at a younger age in prehypertensive adults can result in even greater cost savings.
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Affiliation(s)
- Zhijia Sun
- Department of Epidemiology and Biostatistics (Z.S., Y.D., C.Y., D.S., Y.P., L.L., J.L.), School of Public Health, Peking University, Beijing, China
| | - Haijun Zhang
- Department of Health Policy and Management (H.Z.), School of Public Health, Peking University, Beijing, China
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD (H.Z.)
| | - Yinqi Ding
- Department of Epidemiology and Biostatistics (Z.S., Y.D., C.Y., D.S., Y.P., L.L., J.L.), School of Public Health, Peking University, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics (Z.S., Y.D., C.Y., D.S., Y.P., L.L., J.L.), School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L.L., J.L.)
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China (C.Y., D.S., L.L., J.L.)
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics (Z.S., Y.D., C.Y., D.S., Y.P., L.L., J.L.), School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L.L., J.L.)
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China (C.Y., D.S., L.L., J.L.)
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics (Z.S., Y.D., C.Y., D.S., Y.P., L.L., J.L.), School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L.L., J.L.)
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L.L., J.L.)
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., Y.C., H.D., D.A., Z.C.)
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., Y.C., H.D., D.A., Z.C.)
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., Y.C., H.D., D.A., Z.C.)
| | - Weijie Hu
- Maiji Center for Disease Control and Prevention, Gansu, China (W.H.)
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., Y.C., H.D., D.A., Z.C.)
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China (J.C.)
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, United Kingdom (L.Y., Y.C., H.D., D.A., Z.C.)
| | - Liming Li
- Department of Epidemiology and Biostatistics (Z.S., Y.D., C.Y., D.S., Y.P., L.L., J.L.), School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L.L., J.L.)
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China (C.Y., D.S., L.L., J.L.)
| | - Jun Lv
- Department of Epidemiology and Biostatistics (Z.S., Y.D., C.Y., D.S., Y.P., L.L., J.L.), School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China (C.Y., D.S., Y.P., P.P., L.L., J.L.)
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China (C.Y., D.S., L.L., J.L.)
- State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China (J.L.)
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周 恬, 刘 秋, 张 明, 刘 晓, 康 佳, 沈 鹏, 林 鸿, 唐 迅, 高 培. [Comparison of initiation of antihypertensive therapy strategies for primary prevention of cardiovascular diseases in Chinese population: A decision-analytic Markov modelling study]. BEIJING DA XUE XUE BAO. YI XUE BAN = JOURNAL OF PEKING UNIVERSITY. HEALTH SCIENCES 2024; 56:441-447. [PMID: 38864129 PMCID: PMC11167542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Indexed: 06/13/2024]
Abstract
OBJECTIVE To evaluate the health benefits and intervention efficiency of different strategies of initiating antihypertensive therapy for the primary prevention of cardiovascular diseases in a community-based Chinese population from the Chinese electronic health records research in Yinzhou (CHERRY) study. METHODS A decision-analytic Markov model was used to simulate and compare different antihypertensive initiation strategies, including: Strategy 1, initiation of antihypertensive therapy for Chinese adults with systolic blood pressure (SBP) ≥140 mmHg (2020 Chinese guideline on the primary prevention of cardiovascular diseases); Strategy 2, initiation of antihypertensive therapy for Chinese adults with SBP ≥130 mmHg; Strategy 3, initiation of antihypertensive therapy for Chinese adults with SBP≥140 mmHg, or with SBP between 130 and 140 mmHg and at high risk of cardiovascular diseases (2017 American College of Cardiology/American Heart Association guideline for the prevention, detection, evaluation, and management of high blood pressure in adults); Strategy 4, initiation of antihypertensive therapy for Chinese adults with SBP≥160 mmHg, or with SBP between 140 and 160 mmHg and at high risk of cardiovascular diseases (2019 United Kingdom National Institute for Health and Care Excellence guideline for the hypertension in adults: Diagnosis and management). The high 10-year cardiovascular risk was defined as the predicted risk over 10% based on the 2019 World Health Organization cardiovascular disease risk charts. Different strategies were simulated by the Markov model for ten years (cycles), with parameters mainly from the CHERRY study or published literature. After ten cycles of simulation, the numbers of quality-adjusted life years (QALY), cardiovascular events and all-cause deaths were calculated to evaluate the health benefits of each strategy, and the numbers needed to treat (NNT) for each cardiovascular event or all-cause death could be prevented were calculated to assess the intervention efficiency. One-way sensitivity analysis on the uncertainty of incidence rates of cardiovascular disease and probabilistic sensitivity analysis on the uncertainty of hazard ratios of interventions were conducted. RESULTS A total of 213 987 Chinese adults aged 35-79 years without cardiovascular diseases were included. Compared with strategy 1, the number of cardiovascular events that could be prevented in strategy 2 increased by 666 (95% UI: 334-975), while the NNT per cardiovascular event prevented increased by 10 (95% UI: 7-20). In contrast to strategy 1, the number of cardiovascular events that could be prevented in strategy 3 increased by 388 (95% UI: 194-569), and the NNT per cardiovascular event prevented decreased by 6 (95% UI: 4-12), suggesting that strategy 3 had better health benefits and intervention efficiency. Compared to strategy 1, although the number of cardiovascular events that could be prevented decreased by 193 (95% UI: 98-281) in strategy 4, the NNT per cardiovascular event prevented decreased by 18 (95% UI: 13-37) with better efficiency. The results were consistent in the sensitivity analyses. CONCLUSION When initiating antihypertensive therapy in an economically developed area of China, the strategy combined with cardiovascular risk assessment is more efficient than those purely based on the SBP threshold. The cardiovascular risk assessment strategy with different SBP thresholds is suggested to balance health benefits and intervention efficiency in diverse populations.
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Affiliation(s)
- 恬静 周
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 秋萍 刘
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 明露 张
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 晓非 刘
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 佳丽 康
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
| | - 鹏 沈
- 宁波市鄞州区疾病预防控制中心,浙江宁波 315101Yinzhou District Center for Disease Control and Prevention, Ningbo 315101, Zhejiang, China
| | - 鸿波 林
- 宁波市鄞州区疾病预防控制中心,浙江宁波 315101Yinzhou District Center for Disease Control and Prevention, Ningbo 315101, Zhejiang, China
| | - 迅 唐
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
- 重大疾病流行病学教育部重点实验室(北京大学),北京 100191Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| | - 培 高
- 北京大学公共卫生学院流行病与卫生统计学系,北京 100191Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
- 重大疾病流行病学教育部重点实验室(北京大学),北京 100191Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
- 北京大学临床研究所真实世界证据评价中心,北京 100191Center for Real-world Evidence Evaluation, Peking University Clinical Research Institute, Beijing 100191, China
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