Cardiometabolic-vascular mortality among Chinese adults aged 20 years and older: a national population-based surveillance study, 2013-2021

Cardiometabolic-vascular mortality among Chinese adults aged 20 years and older: a national population-based surveillance study, 2013-2021 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Cardiometabolic-vascular mortality among Chinese adults aged 20 years and older: a national population-based surveillance study, 2013-2021 Binglian Liu, Aowen Chen, Yuting Yang, Changquan Huang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9395619/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background: Diabetes, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease share upstream cardiometabolic pathways, but whether they increasingly form a concentrated adult mortality architecture in China remains unclear. We examined how these four causes jointly shaped mortality among Chinese adults aged 20 years and older from 2013 to 2021 and assessed implications for primary prevention centred on glycaemic and blood-pressure management. Methods: We conducted a national population-based observational analysis using aggregated mortality surveillance data for Chinese adults aged 20 years and older from 2013 to 2021. Because adult-level estimates were synthesised from harmonised 20–59-year and ≥60-year analytic layers with different age-restricted standardisation frameworks, adult structural measures were based on deaths, the percentage of all adult deaths, and the percentage of total weighted adult age-standardised mortality contribution rather than on a pooled adults-20+-only ASMR. We further characterised 2021 life-stage patterns across ages 20–39, 40–59, 60–74, and ≥75 years, and examined later-life inequalities by sex, residence, and region. Results: Combined deaths from the four causes increased from 632,869 in 2013 to 945,427 in 2021. Their share of all adult deaths rose from 44.07% to 50.15%, and their share of total weighted adult ASMR contribution increased from 43.68% to 48.23%. In adults aged 20–59 years, diabetes ASMR increased from 2.83 to 3.78 per 100,000 and ischaemic heart disease ASMR from 19.53 to 21.18, whereas hypertensive heart disease declined from 3.30 to 2.60 and cerebrovascular disease from 28.20 to 24.11. In 2021, weighted rates increased from 0.77, 0.54, 5.37, and 4.51 per 100,000 at ages 20–39 years to 7.20, 4.93, 39.14, and 46.37 at ages 40–59 years, with further escalation in later life. Conclusions: Adult mortality in China is increasingly concentrated within a cardiometabolic–vascular continuum spanning diabetes, blood-pressure-related cardiac injury, and major vascular outcomes. These findings support integrated primary prevention strategies that prioritise glycaemic management, blood-pressure control, and early vascular-risk detection across the adult life course. cardiometabolic mortality diabetes mellitus hypertensive heart disease ischaemic heart disease cerebrovascular disease primary prevention China Figures Figure 1 Figure 2 Figure 3 Figure 4 Research Insights What is currently known about this topic? • CVD dominates adult mortality in China. • Diabetes and hypertension are major upstream drivers. • National studies rarely integrate linked vascular causes. What is the key research question? Do four linked causes form a concentrated adult mortality system in China? What is new? • Four causes accounted for about half of adult deaths by 2021. • Their structural contribution increased from 2013 to 2021. • Patterns progressed from early-adult visibility to later-life concentration. How might this study influence clinical practice? • Findings support integrated glycaemic, blood-pressure, and vascular-risk prevention. Background Adult mortality transition is increasingly shaped by population ageing and the growing dominance of non-communicable diseases over communicable causes.[1,2] In this setting, the public-health question is no longer only whether cardiovascular disease is common, but whether adult mortality is becoming increasingly organised around a limited set of interconnected cardiometabolic and vascular causes. China provides an especially informative setting in which to examine this question. Over recent decades, the country has undergone rapid epidemiological transition, urbanisation, and major shifts in diet, tobacco exposure, adiposity, and chronic disease care.[3–5] At the same time, the integrated national mortality surveillance system has made it possible to examine how adult cause-of-death patterns are being reorganised at population level.[5] Diabetes mellitus, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease merit joint consideration because they represent a clinically coherent continuum rather than unrelated diagnostic entities. Diabetes reflects glycaemic dysregulation and amplifies vascular risk; hypertensive heart disease captures cumulative blood-pressure-related end-organ damage; and ischaemic heart disease and cerebrovascular disease represent the two most important downstream vascular outcomes. These conditions share major upstream drivers, including raised blood pressure, dysglycaemia, adiposity, tobacco exposure, unhealthy diet, and physical inactivity.[6–13] Existing evidence has already established several background facts: cardiovascular disease is the leading cause of death in China; stroke and ischaemic heart disease remain major contributors; diabetes prevalence has risen; and blood-pressure control remains incomplete in many settings.[6–10,14,15] These facts should therefore not be the headline message of the present study. What remains less well characterised is whether adult mortality in China is increasingly concentrated within a four-cause cardiometabolic–vascular system, and how that system is distributed across adult life stages. Most available Chinese studies are disease-specific, all-age analyses, or risk-factor surveys.[4,5,7,14,15] These approaches are valuable but have limited ability to describe a shared adult mortality architecture extending from early adulthood through older age. A life-course perspective is especially relevant because major vascular outcomes in later life may be the cumulative expression of risk accumulation, metabolic dysfunction, and blood-pressure-related injury that become visible much earlier.[8–13,16–18] The present study therefore integrates harmonised mortality surveillance analyses for adults aged 20–59 years and for adults aged 60 years or older. We aimed to quantify the combined burden of diabetes, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease among adults aged 20 years and older in China; to examine how these causes are redistributed across adult life stages; and to assess whether later-life inequalities by sex, residence, and region reflect completely different cause structures or a shared high-burden architecture expressed at different intensities. Methods Study design and data source We performed a national population-based observational study using annual aggregated mortality surveillance data for Chinese adults aged 20 years and older from 1 Jan 2013 to 31 Dec 2021. The surveillance extracts were de-identified, aggregated, and stratified by calendar year, sex, residence (urban or rural), region (eastern, central, or western China), age group, and cause of death.[5] We restricted the analysis to adults aged 20 years and older a priori because the study focused on adult cardiometabolic–vascular mortality architecture rather than all-age mortality. Mortality in childhood and adolescence is epidemiologically distinct and often dominated by causes that are not directly informative for an analysis centred on diabetes-related and blood-pressure-related vascular mortality across adulthood. Cause definitions We examined four focal causes: diabetes mellitus (ICD-10 E10–E14), hypertensive heart disease (ICD-10 I11), ischaemic heart disease (ICD-10 I20–I25), and cerebrovascular disease (ICD-10 I60–I69). These causes were selected because they represent a clinically coherent continuum spanning glycaemic dysregulation, blood-pressure-related cardiac injury, coronary disease, and cerebrovascular disease. Diabetes was retained as a terminal analytic cause because no lower-level subdivision was available in the released hierarchy. Hypertensive heart disease was treated as a distinct signal of cumulative blood-pressure exposure and target-organ injury rather than as an incidental accompaniment to vascular disease. Mortality indicators and adult synthesis For adults aged 20–59 years, cause-specific ASMRs were derived from the harmonised working-age layer using direct standardisation within ages 20–59 years. For adults aged 60 years or older, ASMRs were derived from the later-life analytic layer using the age structure supplied with that surveillance framework. Standard population weights ultimately derive from the 2010 Chinese population census.[19] Because adults-20+-level estimates were synthesised from two age-restricted analytic layers with different standardisation frameworks, adults aged 20 years and older were described using two additive quantities that remain interpretable across layers: total deaths and weighted age-standardised mortality contribution. Weighted contribution represents the original standard-population-weighted contribution of each life-stage layer to adult mortality structure. Accordingly, the principal adult-level structural indicators in this study were the percentage of all-cause deaths in adults aged 20 years and older and the percentage share of total weighted adult ASMR contribution. These quantities do not constitute a de novo pooled adults-20+-only ASMR recalculation. Therefore, cause-specific ASMRs were interpreted within analytically coherent age bands rather than pooled into a single synthetic adults-20+-only ASMR. To characterise the life-course pattern in 2021, we additionally calculated weighted rates for four prespecified adult stages: 20–39 years, 40–59 years, 60–74 years, and ≥75 years. Inequality dimensions and statistical analysis We prespecified sex, residence, and region as inequality dimensions. Because the four focal causes were concentrated in later life, subgroup comparisons in the main analysis focused on adults aged 60 years or older. We also summarised subgroup profiles within adults aged 20–59 years to describe earlier patterns of disadvantage. All analyses were descriptive and population-based. We summarised deaths, crude mortality rates, ASMRs, percentages of all-cause mortality, and weighted adult structural contributions. We deliberately did not use causal language or intervention attribution because the surveillance data were aggregated and were not intended to support individual-level causal inference. Ethics The analysis used publicly available, de-identified, aggregated mortality surveillance data and did not involve contact with human participants or access to identifiable information. Formal ethics committee review and informed consent were therefore not required for this secondary analysis. Use of large language models in manuscript preparation During manuscript preparation, a large language model was used only for language refinement. All scientific content, numerical results, and interpretations were critically reviewed and verified by the authors. Results Increasing concentration of adult mortality in a four-cause cardiometabolic–vascular system, 2013–2021 Between 2013 and 2021, adult mortality in China became increasingly concentrated in the four focal causes (Table 1; Figure 1). Combined deaths from diabetes, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease increased from 632,869 in 2013 to 945,427 in 2021. Their share of all adult deaths rose from 44.07% to 50.15%, indicating that by 2021 approximately one in every two deaths among Chinese adults aged 20 years and older was attributable to this four-cause system. The same pattern was evident when adult mortality structure was examined using weighted age-standardised contribution. The combined share of total weighted adult ASMR contribution increased from 43.68% in 2013 to 48.23% in 2021. Within this adult-level structure, ischaemic heart disease contributed the largest relative increase, rising from 15.57% to 19.45% of the weighted adult mortality structure, while cerebrovascular disease remained the largest single contributor in absolute percentage terms (22.35% and 22.52%, respectively). Table 1. Adult mortality burden of four focal causes in China Cause Deaths 2013 Deaths 2021 % of all adult deaths 2013 % of all adult deaths 2021 % of weighted adult ASMR contribution 2013 % of weighted adult ASMR contribution 2021 Combined four causes 632869 945427 44.07 50.15 43.68 48.23 Diabetes mellitus 26842 50548 1.9 2.7 1.86 2.70 Hypertensive heart disease 56736 72571 4.0 3.9 3.90 3.57 Ischaemic heart disease 225644 384815 15.7 20.4 15.57 19.45 Cerebrovascular disease 323647 437493 22.5 23.2 22.35 22.52 Deaths and percentages refer to adults aged 20 years and older. Weighted adult ASMR contribution is a structural indicator derived from harmonised 20–59-year and ≥60-year layers and should not be interpreted as a pooled adults-20+-only ASMR. Working-age reorganisation and life-stage escalation of cardiometabolic–vascular mortality Within the working-age layer, all-cause ASMR declined from 194.88 per 100,000 in 2013 to 160.31 in 2021, while annual deaths changed little. Yet the internal composition of premature mortality shifted. Diabetes ASMR increased from 2.83 to 3.78 per 100,000 and ischaemic heart disease ASMR increased from 19.53 to 21.18, whereas hypertensive heart disease declined from 3.30 to 2.60 and cerebrovascular disease from 28.20 to 24.11. Thus, the working-age pattern did not simply decline uniformly; it was reorganised toward a stronger diabetes–ischaemic heart disease signal within an already high cerebrovascular burden (Figure 2). The 2021 age profile clarifies where this clustering emerged (Table 2; Figure 3). At ages 20–39 years, weighted mortality rates remained low for diabetes and hypertensive heart disease (0.77 and 0.54 per 100,000) but were already visible for ischaemic heart disease and cerebrovascular disease (5.37 and 4.51 per 100,000). By ages 40–59 years, all four causes had risen markedly, with weighted rates of 7.20 for diabetes, 4.93 for hypertensive heart disease, 39.14 for ischaemic heart disease, and 46.37 for cerebrovascular disease. This midlife clustering indicates that the adult cardiometabolic–vascular continuum becomes clearly identifiable well before old age. Table 2. Life-stage rates for four focal causes in 2021 Adult life stage Diabetes mellitus Hypertensive heart disease Ischaemic heart disease Cerebrovascular disease 20–39 years 0.77 0.54 5.37 4.51 40–59 years 7.20 4.93 39.14 46.37 60–74 years 43.40 34.82 218.19 298.81 ≥75 years 168.10 333.82 1605.70 1730.55 Values are weighted mortality rates per 100,000 population and characterise the shift from early-adult visibility to midlife clustering and later-life concentration. Later-life burden concentration within a shared vascular cause structure In later life, the same four-cause system became highly concentrated rather than diffuse. At ages 60–74 years, weighted rates reached 43.40 per 100,000 for diabetes, 34.82 for hypertensive heart disease, 218.19 for ischaemic heart disease, and 298.81 for cerebrovascular disease (Table 2). Among adults aged ≥75 years, the corresponding rates rose sharply to 168.10, 333.82, 1605.70, and 1730.55 per 100,000, respectively. These values indicate that the cardiometabolic–vascular continuum identified in midlife culminates in a very high later-life mortality concentration. Among adults aged 60 years or older, cerebrovascular disease remained the leading specific cause, declining from 106.87 per 100,000 in 2013 to 88.02 in 2021; ischaemic heart disease changed little in absolute level (74.49 to 75.79), whereas hypertensive heart disease declined from 19.67 to 14.70 and diabetes increased from 8.61 to 9.98. Thus, later-life concentration did not reflect the emergence of wholly new causes, but rather the progressive dominance of a shared vascular cause structure established earlier in adulthood. Sex, residence, and regional inequalities in later-life cardiometabolic–vascular mortality Substantial inequalities were present in later life, but they occurred within a broadly shared cause hierarchy (Table 3; Figure 4). In 2021, all-cause ASMR among adults aged 60 years or older was higher in men than women (439.57 vs 284.57 per 100,000), in rural than urban residents (374.12 vs 325.71), and in western than eastern China (389.48 vs 333.31). Despite these large differences in absolute level, the ranking of focal causes was strikingly consistent across subgroup strata. Cerebrovascular disease and ischaemic heart disease were the two dominant focal causes in every later-life subgroup. Among older men, cerebrovascular disease and ischaemic heart disease reached 105.80 and 85.42 per 100,000, compared with 72.30 and 66.95 among older women. Rural residents had higher later-life ASMRs than urban residents for cerebrovascular disease (95.03 vs 74.66) and ischaemic heart disease (78.58 vs 70.43), while western China had the highest later-life cerebrovascular disease burden (96.13 per 100,000) and central China had the highest ischaemic heart disease burden (88.03). Taken together, these results indicate that later-life inequalities in China are not primarily characterised by completely different cause structures. Rather, the same cardiometabolic–vascular continuum is expressed at higher intensity in already disadvantaged populations. Table 3. Later-life ASMRs by sex, residence, and region, 2021 Dimension Subgroup All-cause ASMR Diabetes mellitus Hypertensive heart disease Ischaemic heart disease Cerebrovascular disease Sex Men 439.57 10.01 15.90 85.42 105.80 Sex Women 284.57 9.93 13.56 66.95 72.30 Residence Urban 325.71 11.26 11.60 70.43 74.66 Residence Rural 374.12 9.30 16.36 78.58 95.03 Region Eastern 333.31 9.43 13.21 70.56 77.76 Region Central 365.98 9.89 16.12 88.03 95.57 Region Western 389.48 11.07 15.41 68.47 96.13 Values are age-standardised mortality rates per 100,000 among adults aged 60 years or older. Discussion This study provides a population-level account of how adult mortality in China is being reorganised within a coherent cardiometabolic–vascular continuum. Four findings stand out. First, diabetes, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease together accounted for an increasingly large share of adult deaths between 2013 and 2021. Second, the continuum did not emerge only in old age; by ages 40–59 years, the four-cause pattern had already become clearly clustered. Third, diabetes became a more visible component of adult mortality structure rather than remaining only a background risk condition. Fourth, later-life inequalities by sex, residence, and region were substantial, but they occurred within a broadly shared cause hierarchy. The first implication is conceptual. Existing national evidence has already shown that cardiovascular disease dominates mortality in China and that stroke and ischaemic heart disease remain the principal specific vascular causes.[6,7,14,15] The present study adds a different message: adult mortality is increasingly concentrated not simply within “cardiovascular disease” in general, but within a limited four-cause system that links glycaemic dysregulation, blood-pressure-related cardiac injury, and two major downstream vascular outcomes. This structural framing is more informative for prevention planning than viewing each cause as an isolated time trend. The second implication concerns timing. The continuum identified here does not begin only in old age. Midlife is the stage at which the four-cause pattern becomes clearly consolidated, and therefore the stage at which prevention opportunities are still substantial. This interpretation is consistent with evidence that major vascular outcomes are driven by a relatively small set of modifiable exposures, especially raised blood pressure, dysglycaemia, adiposity, tobacco exposure, and diet.[8–13,16–18] A life-course prevention strategy therefore means acting earlier, not only caring longer. The role of diabetes warrants specific emphasis. Previous research has already demonstrated that diabetes prevalence in China is high and has increased over time, while diagnosis, treatment, and control remain suboptimal.[9,10] The present findings suggest that diabetes should also be interpreted as a visible component of the adult mortality structure itself. In other words, diabetes is not only an upstream risk state; it is increasingly embedded within the mortality continuum that culminates in coronary and cerebrovascular death. Hypertensive heart disease also deserves more attention than it usually receives in mortality analyses. Although its absolute mortality contribution remained lower than that of ischaemic heart disease and cerebrovascular disease, it provides a population-level signal of cumulative blood-pressure exposure and target-organ injury. This matters in a setting where hypertension prevalence is high and control remains incomplete.[8] Taken together, diabetes and hypertensive heart disease can be understood as upstream and intermediate signals within the same cardiometabolic–vascular architecture rather than as unrelated residual categories. Our inequality findings suggest another important interpretation. Men, rural populations, and western China experienced substantially higher later-life mortality levels, but the dominant focal causes remained remarkably consistent across strata. This pattern suggests that inequality in later-life mortality arises less because different populations die from entirely different diseases, and more because the same cardiometabolic–vascular continuum is expressed at different intensities. That interpretation aligns with broader evidence linking chronic-disease inequality to unequal risk-factor accumulation, unequal preventive care, and socioeconomic disadvantage.[16,17] The study has several strengths. It uses national mortality surveillance data across nine consecutive years, integrates working-age and later-life analyses in one explicit framework, and focuses on a tightly defined group of causes with strong biological and public-health coherence. The inclusion of both structural adult-level indicators and age-stage displays also allows the manuscript to distinguish between overall concentration and life-course redistribution. Several limitations should be recognised. First, the analysis was based on aggregated surveillance data and cannot support individual-level causal inference. Second, adult-level integration relied primarily on deaths and weighted structural contribution because the age-standardisation schemes for the linked working-age and later-life layers were not identical; cause-specific ASMRs therefore should be interpreted within coherent age bands rather than as a pooled synthetic adults-20+-only ASMR. Third, we did not assess disability, treatment trajectories, or non-fatal disease burden. Fourth, although the shared mortality structure suggests common upstream drivers, the present analysis cannot quantify the contribution of specific treatments, control rates, or risk-factor change. Conclusions Adult mortality in China from 2013 to 2021 became increasingly concentrated within a cardiometabolic–vascular continuum composed of diabetes, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease. The continuum emerged clearly in midlife and culminated in pronounced later-life concentration. These findings support integrated primary prevention strategies that align glycaemic management, blood-pressure control, and vascular-risk detection, with particular attention to men, rural populations, and western China. Abbreviations ASMR: age-standardised mortality rate CMR: crude mortality rate HHD: hypertensive heart disease ICD-10: International Classification of Diseases, 10th Revision IHD: ischaemic heart disease Declarations Ethics approval and consent to participate This study used publicly available, de-identified, aggregated mortality surveillance data. No identifiable individual-level information was accessed, and no human participants were contacted. Formal ethics committee review and informed consent were therefore not required for this secondary analysis. Consent for publication Not applicable. Availability of data and materials The data that support the findings of this study are available from the original mortality surveillance data custodian, subject to the permissions and restrictions governing those data. De-identified aggregated analytical data used in this study can be made available from the corresponding author on reasonable request and with permission of the data custodian. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the Sichuan Science and Technology Program (2024YFHZ0011). The funder had no role in study design, data analysis, data interpretation, manuscript preparation, or the decision to submit the work for publication. Authors’ contributions HC and LB conceived the study. YY and CA curated the data. LB and CA directly accessed and verified the data and performed the formal analyses. HC and YY developed the methodology. CA and YY prepared the original draft. HC, LB, and CA critically reviewed and edited the manuscript. HC supervised the study. All authors interpreted the findings and approved the final manuscript. Acknowledgements Not applicable. Authors details 1 West China School of Medicine, Sichuan University, Sichuan University affiliated Chengdu Second People's Hospital,Chengdu Second People's Hospital, No. 10 Qingyun South Street, Chengdu, Sichuan Province, China, 610011 *Correspondence:Huang Changquan, [email protected] References Omran AR. The epidemiologic transition: a theory of the epidemiology of population change. Milbank Q. 2005;83:731–57. GBD 2023 Causes of Death Collaborators. Global burden of 292 causes of death in 204 countries and territories and 660 subnational locations, 1990–2023: a systematic analysis for the Global Burden of Disease Study 2023. Lancet. 2025;406:1811–72. Yang G, Wang Y, Zeng Y, et al. Rapid health transition in China, 1990–2010: findings from the Global Burden of Disease Study 2010. Lancet. 2013;381:1987–2015. Zhou M, Wang H, Zeng X, et al. Mortality, morbidity, and risk factors in China and its provinces, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019;394:1145–58. Liu S, Wu X, Lopez AD, et al. An integrated national mortality surveillance system for death registration and mortality surveillance, China. Bull World Health Organ. 2016;94:46–57. Zhao D, Liu J, Wang M, et al. Epidemiology of cardiovascular disease in China: current features and implications. Nat Rev Cardiol. 2019;16:203–12. Wang W, Liu Y, Liu J, et al. Mortality and years of life lost of cardiovascular diseases in China, 2005–2020: empirical evidence from national mortality surveillance system. Int J Cardiol. 2021;340:105–12. Wang Z, Chen Z, Zhang L, et al. Status of hypertension in China: results from the China Hypertension Survey, 2012–15. Circulation. 2018;137:2344–56. Wang L, Peng W, Zhao Z, et al. Prevalence and treatment of diabetes in China, 2013–2018. JAMA. 2021;326:2498–506. Chan JCN, Lim L-L, Wareham NJ, et al. The Lancet Commission on diabetes: using data to transform diabetes care and patient lives. Lancet. 2021;396:2019–82. Yusuf S, Hawken S, Ounpuu S, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004;364:937–52. Yusuf S, Joseph P, Rangarajan S, et al. Modifiable risk factors, cardiovascular disease, and mortality in 155,722 individuals from 21 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. Lancet. 2020;395:795–808. Li S, Liu Z, Joseph P, et al. Modifiable risk factors associated with cardiovascular disease and mortality in China: a PURE substudy. Eur Heart J. 2022;43:2852–63. GBD 2021 Stroke Risk Factor Collaborators. 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Additional Declarations No competing interests reported. Supplementary Files image1.png Graphical abstract Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 13 May, 2026 Reviewers invited by journal 27 Apr, 2026 Editor assigned by journal 17 Apr, 2026 Submission checks completed at journal 17 Apr, 2026 First submitted to journal 12 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9395619","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633449154,"identity":"7b626ec0-9f2d-4e96-a329-b37afec67804","order_by":0,"name":"Binglian Liu","email":"","orcid":"","institution":"West China School of Medicine, Sichuan University, Sichuan University affiliated Chengdu Second People's Hospital，Chengdu Second People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Binglian","middleName":"","lastName":"Liu","suffix":""},{"id":633449155,"identity":"8513cc8e-2461-4c11-b962-73e2d71a14c5","order_by":1,"name":"Aowen Chen","email":"","orcid":"","institution":"West China School of Medicine, Sichuan University, Sichuan University affiliated Chengdu Second People's Hospital，Chengdu Second People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Aowen","middleName":"","lastName":"Chen","suffix":""},{"id":633449156,"identity":"e3c553a0-6d82-46e3-8632-070722b3f830","order_by":2,"name":"Yuting Yang","email":"","orcid":"","institution":"West China School of Medicine, Sichuan University, Sichuan University affiliated Chengdu Second People's Hospital，Chengdu Second People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuting","middleName":"","lastName":"Yang","suffix":""},{"id":633449157,"identity":"cd19d59f-077b-40d4-90e2-bfc1e29bca05","order_by":3,"name":"Changquan Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYBACAyA+8PEfmxwbe2Pjg4SKGqK0MB6cwcZnzM9zuNngwZljRGlhPszDJpc4c0Z6m+TDFmbCWszZD284zMNjxrjhQGJbRWIDGwN/e3cCXi2WPWkFB+dIpDEbHDjYdiNxhwyDxJmzG/A77AaPwYE3BsfYDA42ArWcYWMwkMglQgtPwn8eg8OMbQWJbczEaTnIc4BNQrKNsY2BOC1ngH6Z2cBmwM/D2CyRcOYYD2G/HD+8+cPHBrb6NvnnDz/+qKiR42/vxa+FAZIAEICHkHJMLaNgFIyCUTAKMAAAFf9Qt7BGcTcAAAAASUVORK5CYII=","orcid":"","institution":"West China School of Medicine, Sichuan University, Sichuan University affiliated Chengdu Second People's Hospital，Chengdu Second People's Hospital","correspondingAuthor":true,"prefix":"","firstName":"Changquan","middleName":"","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2026-04-12 16:08:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9395619/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9395619/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108804539,"identity":"9e25ce2c-82e2-49e1-b025-3bb6b048b3fc","added_by":"auto","created_at":"2026-05-08 15:21:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":104243,"visible":true,"origin":"","legend":"\u003cp\u003eAdult mortality concentration in the four-cause cardiometabolic–vascular system, China, 2013 vs 2021. Panel A shows each cause’s share of all-cause adult deaths in 2013 and 2021. Panel B shows each cause’s share of total weighted adult age-standardised mortality contribution. Combined four-cause share rose from 44.1% to 50.2% for deaths and from 43.7% to 48.2% for weighted adult mortality structure.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9395619/v1/2efc23642a9b89c94d200973.png"},{"id":108583872,"identity":"48572a1b-5616-41c0-8f27-b8d778715d32","added_by":"auto","created_at":"2026-05-06 08:29:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":126244,"visible":true,"origin":"","legend":"\u003cp\u003eWorking-age ASMR trends for four focal causes, 2013-2021. In adults aged 20–59 years, cerebrovascular disease remained the largest single contributor throughout the study period, while diabetes and ischaemic heart disease showed the clearest upward drift in age-standardised mortality rates.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9395619/v1/e2e386bc6232997a08a9bdb6.png"},{"id":108804538,"identity":"51055c1b-6183-4b45-8e99-74c4b142a3dc","added_by":"auto","created_at":"2026-05-08 15:21:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":96594,"visible":true,"origin":"","legend":"\u003cp\u003eAge-specific life-course gradient of cardiometabolic–vascular mortality in 2021. Heat map shows age-specific mortality rates for diabetes, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease across 14 adult age groups. Colour intensity is displayed on a logarithmic scale to preserve readability across the steep late-life gradient.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9395619/v1/f385bbb99f0185f7e7cd7cf8.png"},{"id":108583875,"identity":"7e5116a6-cb33-4655-acdb-9eb0435601ba","added_by":"auto","created_at":"2026-05-06 08:29:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":96736,"visible":true,"origin":"","legend":"\u003cp\u003eLater-life inequalities in four focal causes, 2021. Across all subgroup strata, cerebrovascular disease and ischaemic heart disease remained dominant despite marked inequality in absolute mortality levels.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9395619/v1/b73110c5931f51cc39cc4c50.png"},{"id":108809318,"identity":"bbbcd438-5f19-439b-aa78-b8589a9d7459","added_by":"auto","created_at":"2026-05-08 15:52:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":660879,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9395619/v1/d8264f79-c9b0-49c1-b3f4-6859e3417365.pdf"},{"id":108583870,"identity":"8da74670-3ff3-48b7-903b-42abc9e07a0a","added_by":"auto","created_at":"2026-05-06 08:29:27","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":72705,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical abstract\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9395619/v1/fa8fa37176cae592abfe1e35.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cardiometabolic-vascular mortality among Chinese adults aged 20 years and older: a national population-based surveillance study, 2013-2021","fulltext":[{"header":"Research Insights","content":" \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eWhat is currently known about this topic?\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e• CVD dominates adult mortality in China.\u003cbr\u003e\u0026nbsp;• Diabetes and hypertension are major upstream drivers.\u003cbr\u003e\u0026nbsp;• National studies rarely integrate linked vascular causes.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eWhat is the key research question?\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDo four linked causes form a concentrated adult mortality system in China?\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eWhat is new?\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e• Four causes accounted for about half of adult deaths by 2021.\u003cbr\u003e\u0026nbsp;• Their structural contribution increased from 2013 to 2021.\u003cbr\u003e\u0026nbsp;• Patterns progressed from early-adult visibility to later-life concentration.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHow might this study influence clinical practice?\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e• Findings support integrated glycaemic, blood-pressure, and vascular-risk prevention.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Background","content":"\u003cp\u003eAdult mortality transition is increasingly shaped by population ageing and the growing dominance of non-communicable diseases over communicable causes.[1,2] In this setting, the public-health question is no longer only whether cardiovascular disease is common, but whether adult mortality is becoming increasingly organised around a limited set of interconnected cardiometabolic and vascular causes.\u003c/p\u003e\n\u003cp\u003eChina provides an especially informative setting in which to examine this question. Over recent decades, the country has undergone rapid epidemiological transition, urbanisation, and major shifts in diet, tobacco exposure, adiposity, and chronic disease care.[3–5] At the same time, the integrated national mortality surveillance system has made it possible to examine how adult cause-of-death patterns are being reorganised at population level.[5]\u003c/p\u003e\n\u003cp\u003eDiabetes mellitus, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease merit joint consideration because they represent a clinically coherent continuum rather than unrelated diagnostic entities. Diabetes reflects glycaemic dysregulation and amplifies vascular risk; hypertensive heart disease captures cumulative blood-pressure-related end-organ damage; and ischaemic heart disease and cerebrovascular disease represent the two most important downstream vascular outcomes. These conditions share major upstream drivers, including raised blood pressure, dysglycaemia, adiposity, tobacco exposure, unhealthy diet, and physical inactivity.[6–13]\u003c/p\u003e\n\u003cp\u003eExisting evidence has already established several background facts: cardiovascular disease is the leading cause of death in China; stroke and ischaemic heart disease remain major contributors; diabetes prevalence has risen; and blood-pressure control remains incomplete in many settings.[6–10,14,15] These facts should therefore not be the headline message of the present study. What remains less well characterised is whether adult mortality in China is increasingly concentrated within a four-cause cardiometabolic–vascular system, and how that system is distributed across adult life stages.\u003c/p\u003e\n\u003cp\u003eMost available Chinese studies are disease-specific, all-age analyses, or risk-factor surveys.[4,5,7,14,15] These approaches are valuable but have limited ability to describe a shared adult mortality architecture extending from early adulthood through older age. A life-course perspective is especially relevant because major vascular outcomes in later life may be the cumulative expression of risk accumulation, metabolic dysfunction, and blood-pressure-related injury that become visible much earlier.[8–13,16–18]\u003c/p\u003e\n\u003cp\u003eThe present study therefore integrates harmonised mortality surveillance analyses for adults aged 20–59 years and for adults aged 60 years or older. We aimed to quantify the combined burden of diabetes, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease among adults aged 20 years and older in China; to examine how these causes are redistributed across adult life stages; and to assess whether later-life inequalities by sex, residence, and region reflect completely different cause structures or a shared high-burden architecture expressed at different intensities.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eStudy design and data source\u003c/h2\u003e\n\u003cp\u003eWe performed a national population-based observational study using annual aggregated mortality surveillance data for Chinese adults aged 20 years and older from 1 Jan 2013 to 31 Dec 2021. The surveillance extracts were de-identified, aggregated, and stratified by calendar year, sex, residence (urban or rural), region (eastern, central, or western China), age group, and cause of death.[5]\u003c/p\u003e\n\u003cp\u003eWe restricted the analysis to adults aged 20 years and older a priori because the study focused on adult cardiometabolic–vascular mortality architecture rather than all-age mortality. Mortality in childhood and adolescence is epidemiologically distinct and often dominated by causes that are not directly informative for an analysis centred on diabetes-related and blood-pressure-related vascular mortality across adulthood.\u003c/p\u003e\n\u003ch2\u003eCause definitions\u003c/h2\u003e\n\u003cp\u003eWe examined four focal causes: diabetes mellitus (ICD-10 E10–E14), hypertensive heart disease (ICD-10 I11), ischaemic heart disease (ICD-10 I20–I25), and cerebrovascular disease (ICD-10 I60–I69). These causes were selected because they represent a clinically coherent continuum spanning glycaemic dysregulation, blood-pressure-related cardiac injury, coronary disease, and cerebrovascular disease.\u003c/p\u003e\n\u003cp\u003eDiabetes was retained as a terminal analytic cause because no lower-level subdivision was available in the released hierarchy. Hypertensive heart disease was treated as a distinct signal of cumulative blood-pressure exposure and target-organ injury rather than as an incidental accompaniment to vascular disease.\u003c/p\u003e\n\u003ch2\u003eMortality indicators and adult synthesis\u003c/h2\u003e\n\u003cp\u003eFor adults aged 20–59 years, cause-specific ASMRs were derived from the harmonised working-age layer using direct standardisation within ages 20–59 years. For adults aged 60 years or older, ASMRs were derived from the later-life analytic layer using the age structure supplied with that surveillance framework. Standard population weights ultimately derive from the 2010 Chinese population census.[19]\u003c/p\u003e\n\u003cp\u003eBecause adults-20+-level estimates were synthesised from two age-restricted analytic layers with different standardisation frameworks, adults aged 20 years and older were described using two additive quantities that remain interpretable across layers: total deaths and weighted age-standardised mortality contribution. Weighted contribution represents the original standard-population-weighted contribution of each life-stage layer to adult mortality structure. Accordingly, the principal adult-level structural indicators in this study were the percentage of all-cause deaths in adults aged 20 years and older and the percentage share of total weighted adult ASMR contribution.\u003c/p\u003e\n\u003cp\u003eThese quantities do not constitute a de novo pooled adults-20+-only ASMR recalculation. Therefore, cause-specific ASMRs were interpreted within analytically coherent age bands rather than pooled into a single synthetic adults-20+-only ASMR. To characterise the life-course pattern in 2021, we additionally calculated weighted rates for four prespecified adult stages: 20–39 years, 40–59 years, 60–74 years, and ≥75 years.\u003c/p\u003e\n\u003ch2\u003eInequality dimensions and statistical analysis\u003c/h2\u003e\n\u003cp\u003eWe prespecified sex, residence, and region as inequality dimensions. Because the four focal causes were concentrated in later life, subgroup comparisons in the main analysis focused on adults aged 60 years or older. We also summarised subgroup profiles within adults aged 20–59 years to describe earlier patterns of disadvantage.\u003c/p\u003e\n\u003cp\u003eAll analyses were descriptive and population-based. We summarised deaths, crude mortality rates, ASMRs, percentages of all-cause mortality, and weighted adult structural contributions. We deliberately did not use causal language or intervention attribution because the surveillance data were aggregated and were not intended to support individual-level causal inference.\u003c/p\u003e\n\u003ch2\u003eEthics\u003c/h2\u003e\n\u003cp\u003eThe analysis used publicly available, de-identified, aggregated mortality surveillance data and did not involve contact with human participants or access to identifiable information. Formal ethics committee review and informed consent were therefore not required for this secondary analysis.\u003c/p\u003e\n\u003ch2\u003eUse of large language models in manuscript preparation\u003c/h2\u003e\n\u003cp\u003eDuring manuscript preparation, a large language model was used only for language refinement. All scientific content, numerical results, and interpretations were critically reviewed and verified by the authors.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eIncreasing concentration of adult mortality in a four-cause cardiometabolic\u0026ndash;vascular system, 2013\u0026ndash;2021\u003c/h2\u003e\n\u003cp\u003eBetween 2013 and 2021, adult mortality in China became increasingly concentrated in the four focal causes (Table 1; Figure 1). Combined deaths from diabetes, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease increased from 632,869 in 2013 to 945,427 in 2021. Their share of all adult deaths rose from 44.07% to 50.15%, indicating that by 2021 approximately one in every two deaths among Chinese adults aged 20 years and older was attributable to this four-cause system.\u003c/p\u003e\n\u003cp\u003eThe same pattern was evident when adult mortality structure was examined using weighted age-standardised contribution. The combined share of total weighted adult ASMR contribution increased from 43.68% in 2013 to 48.23% in 2021. Within this adult-level structure, ischaemic heart disease contributed the largest relative increase, rising from 15.57% to 19.45% of the weighted adult mortality structure, while cerebrovascular disease remained the largest single contributor in absolute percentage terms (22.35% and 22.52%, respectively).\u003c/p\u003e\n\u003cp\u003eTable 1. Adult mortality burden of four focal causes in China\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCause\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeaths 2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeaths 2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% of all adult deaths 2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% of all adult deaths 2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% of weighted adult ASMR contribution 2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% of weighted adult ASMR contribution 2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCombined four causes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e632869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e945427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e44.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e50.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e43.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e48.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003eDiabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e26842\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e50548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e2.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003eHypertensive heart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e56736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e72571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e3.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e3.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003eIschaemic heart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e225644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e384815\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e15.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e20.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e15.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e19.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003eCerebrovascular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e323647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e437493\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e22.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e23.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e22.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e22.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDeaths and percentages refer to adults aged 20 years and older. Weighted adult ASMR contribution is a structural indicator derived from harmonised 20\u0026ndash;59-year and \u0026ge;60-year layers and should not be interpreted as a pooled adults-20+-only ASMR.\u003c/p\u003e\n\u003ch2\u003eWorking-age reorganisation and life-stage escalation of cardiometabolic\u0026ndash;vascular mortality\u003c/h2\u003e\n\u003cp\u003eWithin the working-age layer, all-cause ASMR declined from 194.88 per 100,000 in 2013 to 160.31 in 2021, while annual deaths changed little. Yet the internal composition of premature mortality shifted. Diabetes ASMR increased from 2.83 to 3.78 per 100,000 and ischaemic heart disease ASMR increased from 19.53 to 21.18, whereas hypertensive heart disease declined from 3.30 to 2.60 and cerebrovascular disease from 28.20 to 24.11. Thus, the working-age pattern did not simply decline uniformly; it was reorganised toward a stronger diabetes\u0026ndash;ischaemic heart disease signal within an already high cerebrovascular burden (Figure 2).\u003c/p\u003e\n\u003cp\u003eThe 2021 age profile clarifies where this clustering emerged (Table 2; Figure 3). At ages 20\u0026ndash;39 years, weighted mortality rates remained low for diabetes and hypertensive heart disease (0.77 and 0.54 per 100,000) but were already visible for ischaemic heart disease and cerebrovascular disease (5.37 and 4.51 per 100,000). By ages 40\u0026ndash;59 years, all four causes had risen markedly, with weighted rates of 7.20 for diabetes, 4.93 for hypertensive heart disease, 39.14 for ischaemic heart disease, and 46.37 for cerebrovascular disease. This midlife clustering indicates that the adult cardiometabolic\u0026ndash;vascular continuum becomes clearly identifiable well before old age.\u003c/p\u003e\n\u003cp\u003eTable 2. Life-stage rates for four focal causes in 2021\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdult life stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes mellitus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertensive heart disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIschaemic heart disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCerebrovascular disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e20\u0026ndash;39 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e5.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e4.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e40\u0026ndash;59 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e7.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e39.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e46.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e60\u0026ndash;74 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e43.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e34.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e218.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e298.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026ge;75 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e168.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e333.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1605.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1730.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are weighted mortality rates per 100,000 population and characterise the shift from early-adult visibility to midlife clustering and later-life concentration.\u003c/p\u003e\n\u003ch2\u003eLater-life burden concentration within a shared vascular cause structure\u003c/h2\u003e\n\u003cp\u003eIn later life, the same four-cause system became highly concentrated rather than diffuse. At ages 60\u0026ndash;74 years, weighted rates reached 43.40 per 100,000 for diabetes, 34.82 for hypertensive heart disease, 218.19 for ischaemic heart disease, and 298.81 for cerebrovascular disease (Table 2). Among adults aged \u0026ge;75 years, the corresponding rates rose sharply to 168.10, 333.82, 1605.70, and 1730.55 per 100,000, respectively. These values indicate that the cardiometabolic\u0026ndash;vascular continuum identified in midlife culminates in a very high later-life mortality concentration.\u003c/p\u003e\n\u003cp\u003eAmong adults aged 60 years or older, cerebrovascular disease remained the leading specific cause, declining from 106.87 per 100,000 in 2013 to 88.02 in 2021; ischaemic heart disease changed little in absolute level (74.49 to 75.79), whereas hypertensive heart disease declined from 19.67 to 14.70 and diabetes increased from 8.61 to 9.98. Thus, later-life concentration did not reflect the emergence of wholly new causes, but rather the progressive dominance of a shared vascular cause structure established earlier in adulthood.\u003c/p\u003e\n\u003ch2\u003eSex, residence, and regional inequalities in later-life cardiometabolic\u0026ndash;vascular mortality\u003c/h2\u003e\n\u003cp\u003eSubstantial inequalities were present in later life, but they occurred within a broadly shared cause hierarchy (Table 3; Figure 4). In 2021, all-cause ASMR among adults aged 60 years or older was higher in men than women (439.57 vs 284.57 per 100,000), in rural than urban residents (374.12 vs 325.71), and in western than eastern China (389.48 vs 333.31).\u003c/p\u003e\n\u003cp\u003eDespite these large differences in absolute level, the ranking of focal causes was strikingly consistent across subgroup strata. Cerebrovascular disease and ischaemic heart disease were the two dominant focal causes in every later-life subgroup. Among older men, cerebrovascular disease and ischaemic heart disease reached 105.80 and 85.42 per 100,000, compared with 72.30 and 66.95 among older women. Rural residents had higher later-life ASMRs than urban residents for cerebrovascular disease (95.03 vs 74.66) and ischaemic heart disease (78.58 vs 70.43), while western China had the highest later-life cerebrovascular disease burden (96.13 per 100,000) and central China had the highest ischaemic heart disease burden (88.03).\u003c/p\u003e\n\u003cp\u003eTaken together, these results indicate that later-life inequalities in China are not primarily characterised by completely different cause structures. Rather, the same cardiometabolic\u0026ndash;vascular continuum is expressed at higher intensity in already disadvantaged populations.\u003c/p\u003e\n\u003cp\u003eTable 3. Later-life ASMRs by sex, residence, and region, 2021\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDimension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubgroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll-cause ASMR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes mellitus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertensive heart disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIschaemic heart disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCerebrovascular disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eMen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e439.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e10.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e15.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e85.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e105.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e284.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e9.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e13.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e66.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e72.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e325.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e11.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e11.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e70.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e74.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e374.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e9.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e16.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e78.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e95.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eEastern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e333.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e9.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e13.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e70.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e77.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eCentral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e365.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e9.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e16.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e88.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e95.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003eWestern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e389.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e11.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e15.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e68.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e96.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eValues are age-standardised mortality rates per 100,000 among adults aged 60 years or older.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides a population-level account of how adult mortality in China is being reorganised within a coherent cardiometabolic–vascular continuum. Four findings stand out. First, diabetes, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease together accounted for an increasingly large share of adult deaths between 2013 and 2021. Second, the continuum did not emerge only in old age; by ages 40–59 years, the four-cause pattern had already become clearly clustered. Third, diabetes became a more visible component of adult mortality structure rather than remaining only a background risk condition. Fourth, later-life inequalities by sex, residence, and region were substantial, but they occurred within a broadly shared cause hierarchy.\u003c/p\u003e\n\u003cp\u003eThe first implication is conceptual. Existing national evidence has already shown that cardiovascular disease dominates mortality in China and that stroke and ischaemic heart disease remain the principal specific vascular causes.[6,7,14,15] The present study adds a different message: adult mortality is increasingly concentrated not simply within “cardiovascular disease” in general, but within a limited four-cause system that links glycaemic dysregulation, blood-pressure-related cardiac injury, and two major downstream vascular outcomes. This structural framing is more informative for prevention planning than viewing each cause as an isolated time trend.\u003c/p\u003e\n\u003cp\u003eThe second implication concerns timing. The continuum identified here does not begin only in old age. Midlife is the stage at which the four-cause pattern becomes clearly consolidated, and therefore the stage at which prevention opportunities are still substantial. This interpretation is consistent with evidence that major vascular outcomes are driven by a relatively small set of modifiable exposures, especially raised blood pressure, dysglycaemia, adiposity, tobacco exposure, and diet.[8–13,16–18] A life-course prevention strategy therefore means acting earlier, not only caring longer.\u003c/p\u003e\n\u003cp\u003eThe role of diabetes warrants specific emphasis. Previous research has already demonstrated that diabetes prevalence in China is high and has increased over time, while diagnosis, treatment, and control remain suboptimal.[9,10] The present findings suggest that diabetes should also be interpreted as a visible component of the adult mortality structure itself. In other words, diabetes is not only an upstream risk state; it is increasingly embedded within the mortality continuum that culminates in coronary and cerebrovascular death.\u003c/p\u003e\n\u003cp\u003eHypertensive heart disease also deserves more attention than it usually receives in mortality analyses. Although its absolute mortality contribution remained lower than that of ischaemic heart disease and cerebrovascular disease, it provides a population-level signal of cumulative blood-pressure exposure and target-organ injury. This matters in a setting where hypertension prevalence is high and control remains incomplete.[8] Taken together, diabetes and hypertensive heart disease can be understood as upstream and intermediate signals within the same cardiometabolic–vascular architecture rather than as unrelated residual categories.\u003c/p\u003e\n\u003cp\u003eOur inequality findings suggest another important interpretation. Men, rural populations, and western China experienced substantially higher later-life mortality levels, but the dominant focal causes remained remarkably consistent across strata. This pattern suggests that inequality in later-life mortality arises less because different populations die from entirely different diseases, and more because the same cardiometabolic–vascular continuum is expressed at different intensities. That interpretation aligns with broader evidence linking chronic-disease inequality to unequal risk-factor accumulation, unequal preventive care, and socioeconomic disadvantage.[16,17]\u003c/p\u003e\n\u003cp\u003eThe study has several strengths. It uses national mortality surveillance data across nine consecutive years, integrates working-age and later-life analyses in one explicit framework, and focuses on a tightly defined group of causes with strong biological and public-health coherence. The inclusion of both structural adult-level indicators and age-stage displays also allows the manuscript to distinguish between overall concentration and life-course redistribution.\u003c/p\u003e\n\u003cp\u003eSeveral limitations should be recognised. First, the analysis was based on aggregated surveillance data and cannot support individual-level causal inference. Second, adult-level integration relied primarily on deaths and weighted structural contribution because the age-standardisation schemes for the linked working-age and later-life layers were not identical; cause-specific ASMRs therefore should be interpreted within coherent age bands rather than as a pooled synthetic adults-20+-only ASMR. Third, we did not assess disability, treatment trajectories, or non-fatal disease burden. Fourth, although the shared mortality structure suggests common upstream drivers, the present analysis cannot quantify the contribution of specific treatments, control rates, or risk-factor change.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eAdult mortality in China from 2013 to 2021 became increasingly concentrated within a cardiometabolic–vascular continuum composed of diabetes, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease. The continuum emerged clearly in midlife and culminated in pronounced later-life concentration. These findings support integrated primary prevention strategies that align glycaemic management, blood-pressure control, and vascular-risk detection, with particular attention to men, rural populations, and western China.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eASMR:\u0026nbsp;\u003c/strong\u003eage-standardised mortality rate\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCMR:\u0026nbsp;\u003c/strong\u003ecrude mortality rate\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHHD:\u0026nbsp;\u003c/strong\u003ehypertensive heart disease\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eICD-10:\u0026nbsp;\u003c/strong\u003eInternational Classification of Diseases, 10th Revision\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIHD:\u0026nbsp;\u003c/strong\u003eischaemic heart disease\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThis study used publicly available, de-identified, aggregated mortality surveillance data. No identifiable individual-level information was accessed, and no human participants were contacted. Formal ethics committee review and informed consent were therefore not required for this secondary analysis.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the original mortality surveillance data custodian, subject to the permissions and restrictions governing those data. De-identified aggregated analytical data used in this study can be made available from the corresponding author on reasonable request and with permission of the data custodian.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the Sichuan Science and Technology Program (2024YFHZ0011). The funder had no role in study design, data analysis, data interpretation, manuscript preparation, or the decision to submit the work for publication.\u003c/p\u003e\n\u003ch2\u003eAuthors’ contributions\u003c/h2\u003e\n\u003cp\u003eHC and LB conceived the study. YY and CA curated the data. LB and CA directly accessed and verified the data and performed the formal analyses. HC and YY developed the methodology. CA and YY prepared the original draft. HC, LB, and CA critically reviewed and edited the manuscript. HC supervised the study. All authors interpreted the findings and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAuthors details\u003c/h2\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e West China School of Medicine, Sichuan University, Sichuan University affiliated Chengdu Second People's Hospital,Chengdu Second People's Hospital, No. 10 Qingyun South Street, Chengdu, Sichuan Province, China, 610011\u003c/p\u003e\n\u003cp\u003e*Correspondence:Huang Changquan,[email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOmran AR. The epidemiologic transition: a theory of the epidemiology of population change. Milbank Q. 2005;83:731\u0026ndash;57.\u003c/li\u003e\n\u003cli\u003eGBD 2023 Causes of Death Collaborators. Global burden of 292 causes of death in 204 countries and territories and 660 subnational locations, 1990\u0026ndash;2023: a systematic analysis for the Global Burden of Disease Study 2023. Lancet. 2025;406:1811\u0026ndash;72.\u003c/li\u003e\n\u003cli\u003eYang G, Wang Y, Zeng Y, et al. Rapid health transition in China, 1990\u0026ndash;2010: findings from the Global Burden of Disease Study 2010. Lancet. 2013;381:1987\u0026ndash;2015.\u003c/li\u003e\n\u003cli\u003eZhou M, Wang H, Zeng X, et al. Mortality, morbidity, and risk factors in China and its provinces, 1990\u0026ndash;2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019;394:1145\u0026ndash;58.\u003c/li\u003e\n\u003cli\u003eLiu S, Wu X, Lopez AD, et al. An integrated national mortality surveillance system for death registration and mortality surveillance, China. Bull World Health Organ. 2016;94:46\u0026ndash;57.\u003c/li\u003e\n\u003cli\u003eZhao D, Liu J, Wang M, et al. Epidemiology of cardiovascular disease in China: current features and implications. Nat Rev Cardiol. 2019;16:203\u0026ndash;12.\u003c/li\u003e\n\u003cli\u003eWang W, Liu Y, Liu J, et al. Mortality and years of life lost of cardiovascular diseases in China, 2005\u0026ndash;2020: empirical evidence from national mortality surveillance system. Int J Cardiol. 2021;340:105\u0026ndash;12.\u003c/li\u003e\n\u003cli\u003eWang Z, Chen Z, Zhang L, et al. Status of hypertension in China: results from the China Hypertension Survey, 2012\u0026ndash;15. Circulation. 2018;137:2344\u0026ndash;56.\u003c/li\u003e\n\u003cli\u003eWang L, Peng W, Zhao Z, et al. Prevalence and treatment of diabetes in China, 2013\u0026ndash;2018. JAMA. 2021;326:2498\u0026ndash;506.\u003c/li\u003e\n\u003cli\u003eChan JCN, Lim L-L, Wareham NJ, et al. The Lancet Commission on diabetes: using data to transform diabetes care and patient lives. Lancet. 2021;396:2019\u0026ndash;82.\u003c/li\u003e\n\u003cli\u003eYusuf S, Hawken S, Ounpuu S, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004;364:937\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eYusuf S, Joseph P, Rangarajan S, et al. Modifiable risk factors, cardiovascular disease, and mortality in 155,722 individuals from 21 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. Lancet. 2020;395:795\u0026ndash;808.\u003c/li\u003e\n\u003cli\u003eLi S, Liu Z, Joseph P, et al. Modifiable risk factors associated with cardiovascular disease and mortality in China: a PURE substudy. Eur Heart J. 2022;43:2852\u0026ndash;63.\u003c/li\u003e\n\u003cli\u003eGBD 2021 Stroke Risk Factor Collaborators. Global, regional, and national burden of stroke and its risk factors, 1990\u0026ndash;2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Neurol. 2024;23:973\u0026ndash;1003.\u003c/li\u003e\n\u003cli\u003eWang YJ, Li ZX, Gu HQ, et al. China Stroke Statistics 2019. Stroke Vasc Neurol. 2020;5:211\u0026ndash;39.\u003c/li\u003e\n\u003cli\u003eLi Y, Wang DD, Ley SH, et al. Can China achieve a one-third reduction in premature mortality from non-communicable diseases by 2030? BMC Med. 2017;15:132.\u003c/li\u003e\n\u003cli\u003eAllen L, Williams J, Townsend N, et al. Socioeconomic status and non-communicable disease behavioural risk factors in low-income and lower-middle-income countries: a systematic review. Lancet Glob Health. 2017;5:e277\u0026ndash;89.\u003c/li\u003e\n\u003cli\u003eMagnussen C, Ojeda FM, Leong DP, et al. Global effect of modifiable risk factors on cardiovascular disease and mortality. N Engl J Med. 2023;389:1273\u0026ndash;85.\u003c/li\u003e\n\u003cli\u003eNational Bureau of Statistics of China. Tabulation on the 2010 population census of the People\u0026rsquo;s Republic of China. Beijing: China Statistics Press; 2012.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"diabetology-and-metabolic-syndrome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dims","sideBox":"Learn more about [Diabetology \u0026 Metabolic Syndrome](http://dmsjournal.biomedcentral.com/)","snPcode":"13098","submissionUrl":"https://submission.nature.com/new-submission/13098/3","title":"Diabetology \u0026 Metabolic Syndrome","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"cardiometabolic mortality; diabetes mellitus, hypertensive heart disease, ischaemic heart disease, cerebrovascular disease, primary prevention, China","lastPublishedDoi":"10.21203/rs.3.rs-9395619/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9395619/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eDiabetes, hypertensive heart disease, ischaemic heart disease, and cerebrovascular disease share upstream cardiometabolic pathways, but whether they increasingly form a concentrated adult mortality architecture in China remains unclear. We examined how these four causes jointly shaped mortality among Chinese adults aged 20 years and older from 2013 to 2021 and assessed implications for primary prevention centred on glycaemic and blood-pressure management.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe conducted a national population-based observational analysis using aggregated mortality surveillance data for Chinese adults aged 20 years and older from 2013 to 2021. Because adult-level estimates were synthesised from harmonised 20–59-year and ≥60-year analytic layers with different age-restricted standardisation frameworks, adult structural measures were based on deaths, the percentage of all adult deaths, and the percentage of total weighted adult age-standardised mortality contribution rather than on a pooled adults-20+-only ASMR. We further characterised 2021 life-stage patterns across ages 20–39, 40–59, 60–74, and ≥75 years, and examined later-life inequalities by sex, residence, and region.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eCombined deaths from the four causes increased from 632,869 in 2013 to 945,427 in 2021. Their share of all adult deaths rose from 44.07% to 50.15%, and their share of total weighted adult ASMR contribution increased from 43.68% to 48.23%. In adults aged 20–59 years, diabetes ASMR increased from 2.83 to 3.78 per 100,000 and ischaemic heart disease ASMR from 19.53 to 21.18, whereas hypertensive heart disease declined from 3.30 to 2.60 and cerebrovascular disease from 28.20 to 24.11. In 2021, weighted rates increased from 0.77, 0.54, 5.37, and 4.51 per 100,000 at ages 20–39 years to 7.20, 4.93, 39.14, and 46.37 at ages 40–59 years, with further escalation in later life.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eAdult mortality in China is increasingly concentrated within a cardiometabolic–vascular continuum spanning diabetes, blood-pressure-related cardiac injury, and major vascular outcomes. These findings support integrated primary prevention strategies that prioritise glycaemic management, blood-pressure control, and early vascular-risk detection across the adult life course.\u003c/p\u003e","manuscriptTitle":"Cardiometabolic-vascular mortality among Chinese adults aged 20 years and older: a national population-based surveillance study, 2013-2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-06 08:29:23","doi":"10.21203/rs.3.rs-9395619/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"198911257269356494280597289893299509458","date":"2026-05-14T00:07:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-27T18:13:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-17T13:54:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-17T13:54:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"Diabetology \u0026 Metabolic Syndrome","date":"2026-04-12T15:54:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"diabetology-and-metabolic-syndrome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dims","sideBox":"Learn more about [Diabetology \u0026 Metabolic Syndrome](http://dmsjournal.biomedcentral.com/)","snPcode":"13098","submissionUrl":"https://submission.nature.com/new-submission/13098/3","title":"Diabetology \u0026 Metabolic Syndrome","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dae573c0-c6c6-493a-91ea-7fe833a3a373","owner":[],"postedDate":"May 6th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"198911257269356494280597289893299509458","date":"2026-05-14T00:07:07+00:00","index":37,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T08:29:23+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-06 08:29:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9395619","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9395619","identity":"rs-9395619","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}