Skip main navigation

Future Cardiovascular Disease in China

Markov Model and Risk Factor Scenario Projections From the Coronary Heart Disease Policy Model–China
Originally published Cardiovascular Quality and Outcomes. 2010;3:243–252


Background— The relative effects of individual and combined risk factor trends on future cardiovascular disease in China have not been quantified in detail.

Methods and Results— Future risk factor trends in China were projected based on prior trends. Cardiovascular disease (coronary heart disease and stroke) in adults ages 35 to 84 years was projected from 2010 to 2030 using the Coronary Heart Disease Policy Model–China, a Markov computer simulation model. With risk factor levels held constant, projected annual cardiovascular events increased by >50% between 2010 and 2030 based on population aging and growth alone. Projected trends in blood pressure, total cholesterol, diabetes (increases), and active smoking (decline) would increase annual cardiovascular disease events by an additional 23%, an increase of approximately 21.3 million cardiovascular events and 7.7 million cardiovascular deaths over 2010 to 2030. Aggressively reducing active smoking in Chinese men to 20% prevalence in 2020 and 10% prevalence in 2030 or reducing mean systolic blood pressure by 3.8 mm Hg in men and women would counteract adverse trends in other risk factors by preventing cardiovascular events and 2.9 to 5.7 million total deaths over 2 decades.

Conclusions— Aging and population growth will increase cardiovascular disease by more than a half over the coming 20 years, and projected unfavorable trends in blood pressure, total cholesterol, diabetes, and body mass index may accelerate the epidemic. National policy aimed at controlling blood pressure, smoking, and other risk factors would counteract the expected future cardiovascular disease epidemic in China.

Since the beginning of economic and social reforms in 1979, China has increased its standard of living and life expectancy. Cardiovascular disease, principally stroke and coronary heart disease (CHD), is the leading cause of death and is expected to increase with further economic development and urbanization, aging of the population, and changes in diet and physical activity1,2 that will predispose many Chinese to high blood pressure, overweight, dyslipidemia, and diabetes.3,4 Though male smoking prevalence has declined by more than 10% since the mid-1980s, 62% of Chinese men smoke actively, and at least 49% of nonsmokers (predominantly women) are exposed to passive smoking at home or at work.5 Others have estimated the impact of risk factors on cardiovascular risk,6–8 and overall cardiovascular disease in China,9,10 but prior research has not focused on individual or synergistic effects of risk factors on future cardiovascular disease on a national scale. Building on our predictions of the impact of expected demographic changes on CHD,11 we forecast the impact of projected future risk factor trends on CHD and stroke in China from 2010 to 2030.

Editorial see p 226


  • It is certain that aging of the Chinese population will result in increased numbers of stroke and coronary heart disease events in future years.

  • Population-based surveys since China’s economic reforms in the early 1980s suggest increasing trends in blood pressure, cholesterol, and diabetes, countered by a slight decline in smoking in men.

  • Projecting the cardiovascular disease impact of future risk factor trends can point toward best prevention policies.


  • This computer modeling study is the first to use past survey data to project a range of likely scenarios for the effects of future individual and combined risk factor trends on cardiovascular disease in China.

  • Aging of the population is inevitable, but the projected additional impact of unfavorable risk factors is potentially reversible.


The CHD Policy Model–China

The CHD Policy-China is a Markov (state-transition) model of cardiovascular disease in the adult Chinese population.11 Means and proportions of cardiovascular disease risk factors in Chinese adults in 10-year age categories ages 35 to 84 years in 2000 were estimated from the International Collaborative Study of Cardiovascular Disease in Asia Study (InterASIA).12 Age trends in risk factor levels were preserved over time. Stroke incidence,13,14 mortality,15 and case-fatality13 estimates were derived from other Chinese studies (supplemental Appendix Table 1). Multivariate CHD and ischemic stroke hazard ratios for age, sex, systolic blood pressure (SBP), total cholesterol (TC), active cigarette smoking, high density lipoprotein (HDL) cholesterol, diabetes, and body mass index (BMI) were estimated from the China Multiprovincial Cohort Study (CMCS, supplemental Appendix Table 2).6 Cox proportional hazard models for hemorrhagic stroke (same risk factors excepting cholesterol, BMI, and diabetes) and noncardiovascular death (same excepting cholesterol and BMI) were also estimated from CMCS. Significant (P<0.05) age×risk factor interactions observed for smoking in CHD proportional hazards models, SBP, smoking, and diabetes in ischemic stroke models, smoking and SBP for hemorrhagic stroke models and smoking and diabetes in noncardiovascular mortality models were incorporated in age-specific risk coefficients.

For the main analysis, we assumed BMI effects on cardiovascular risk were mediated through other risk factors: the effect of a 1 kg/m2 increase in BMI on SBP (males, 1.36 mm Hg; females, 1.40 mm Hg), TC (males and females, 0.05 mmol/L), and HDL (males, −0.03 mmol/L; females, −0.02 mmol/L) were estimated from InterASIA. We assumed 1 kg/m2 increase in BMI would lead to a 0.21% absolute increase in diabetes prevalence.16

The main outcomes predicted were CHD events (nonfatal and nonfatal first-ever and repeat episodes of stable and unstable angina, myocardial infarction, or cardiac arrest) and stroke events (nonfatal and fatal ischemic and hemorrhagic strokes). CHD deaths, stroke deaths, and noncardiovascular deaths (total mortality−stroke and CHD mortality) are reported in the supplemental Appendix. “Cardiovascular disease” was defined as combined CHD, ischemic stroke, and hemorrhagic stroke.

CHD Risk Factor Trend Analysis (2010 to 2030)

Based on secular trends in SBP, TC, active smoking, BMI, and diabetes analyzed from 1980 to 2006 (supplemental Appendix Tables 3 and 4, supplemental Appendix Figure 1) future risk factor trends for the population ages 35 to 84 years were projected forward over 2010 to 2030 (Table 1 and supplemental Appendix Figure 2a–2e). HDL and passive smoking trends were not analyzed due to lack of reliable past data. Unless otherwise noted, the nationally representative InterASIA survey value served as the intercept in 2000. To ensure historical consistency and biological plausibility, it was decided a priori that in the main analysis no projected trend exceeded the most extreme adult population value in Japanese or Korean national surveys since 1960.21 Linear main SBP, active smoking, and BMI trends were estimated from six China Health and Nutrition Survey (CHNS)17 surveys 1991 to 2006 using an age-adjusted random effects model assuming clustering at the level of the individual study participant. Other SBP, smoking, and BMI scenarios were based on alternate trends suggested by CHNS data. Age×time interactions observed in trends for SBP, BMI, or active smoking were incorporated into age-specific risk factor trend projections. TC and diabetes projections were based on a number of past surveys, and a logistic trend function reaching a predetermined ceiling value was used for the main and high trends. There were insufficient data for assessing age×time interactions for TC or diabetes. Trend analyses were conducted using Stata (Statacorp, Austin, Tex) and Excel (Microsoft, Redmond, Wash).

Table 1. Future Trends in Selected CHD and Stroke Risk Factors in Chinese Adults 2000 to 2030, Based on Observed Survey Trends During 1980 to 2006: Means or Proportions Age-Standardized for Ages 35 to 84 Directly From the 2000 Chinese Census

ScenarioDefinitionTrend FunctionStart Value 2000End Value 2030
M indicates male; F, female. Unlabeled values are for both men and women.
*Logistic trend functions TC: Main=1.1×[Exp(0.1×year-2000)/(1+Exp(0.1×year-2000)], High=1.3×[Exp(0.22×year-2000)/(1+Exp(0.22×year-2000)].
†Logistic trend functions diabetes: Main=15×[Exp(0.19×year-2000)/(1+Exp(0.19×year-2000)], High=22×[Exp(0.21×year-2000)/(1+Exp(0.21×year-2000)].
‡Exponential trend function BMI: High males=21.61×Exp(0.006×year), females=22.11×EXP (0.005×year).
Base caseRisk factors constant at 2000 levels
Trend cases
    SBP, mm HgEstimated from China Health and Nutrition Survey (CHNS)17 except low scenario based on US national surveys 1990–200218
        MainM +0.21 annuallyLinearM 126.7M 134.0
F +0.17 annuallyF 124.9F 133.2
        HighM +0.26 annuallyLinearM 135.7
F +0.21 annuallyF 131.4
        Low−0.14 annually (decline)18LinearM 122.3
F 120.5
    TC, mmol/LMain and high followed Sino-MONICA Beijing trend19 to prespecified ceiling, low followed Beijing professionals20 trend
        MainRise to ceiling of 5.4* (US surveys peak)18Logistic*M 4.7M 5.3
F 4.8F 5.4
        HighRise to ceiling of 5.7* (Japanese surveys peak)21Logistic*M 5.7
F 5.7
        LowM +0.008 annuallyLinearM 5.0
F +0.006 annuallyF 5.0
    Smoking, % prevalenceEstimated from CHNS, except worst case in females based on Japanese surveys21
        MainM −0.58% annuallyLinearM 59.8%M 36.6%
F −0.13% annuallyF 7.1%F 1.9%
        WorstM −0.33% annuallyLinearM 46.6%
F +0.30% annually (increase)F 19.0%
        BestM −0.83% annuallyLinearM 26.6%
F −0.19% annuallyF 0.2%
    Diabetes, % prevalenceMain and high assumed steep increase seen between national surveys22–24 to prespecified ceiling, low based on past prevalence and urbanization.25 Higher prevalence based on combined fasting glucose and oral glucose tolerance test26
        MainRise to ceiling of 15% prevalence (peak in United States)18LogisticM 5.3%M 14.8%
F 6.1%F 15.6%
        HighStart at higher prevalence 2000, 26 rise to ceiling of 22% (peak in Japan) 21LogisticM 5.8%F 5.6%M 20.4%F 21.5%
        LowM +0.08 annuallyLinearM 5.3%M 8.1%
F +0.08 annuallyF 6.1%F 9.0%
    BMI, kg/m2Main trend estimated from CHNS, effects mediated through downstream changes in SBP, TC, HDL cholesterol, and diabetes
        MainM +0.10 annuallyLinearM 23.1M 26.4
F +0.09 annuallyF 23.5F 26.4
        HighExponential increase, similar to short-term increases in the United States27ExponentialM 28.7F 29.0
        Low0.88×ln (year)Log-linearM 24.9
F 25.6

The CHD Policy Model–China simulated effects of projected risk factor trends on cardiovascular disease over 2010 to 2030. A base case simulated cardiovascular disease events over 2010 to 2030 with risk factors held at year 2000 levels. The base case proportion of CHD, stroke, and cardiovascular disease explained by individual risk factors was determined by running a simulation simultaneously setting all risk factors at optimal levels28 [zero smoking and diabetes exposures and lowest risk levels of BMI,29 cholesterol,30 and blood pressure31 (supplemental Appendix, Figure 1)]. Subsequently, risk factor trend scenario simulations were run and incremental changes in cardiovascular disease events calculated by comparing the trend cases with the base case.

Sensitivity Analyses

One-way sensitivity analyses explored uncertainty about main analysis trend projections and potential benefits of controlling smoking or SBP. Risk factor β-coefficients estimated from Framingham Heart Study data (supplemental Appendix Table 2) were substituted for CMCS coefficients. Based on evidence from CMCS, a simulation assumed additional BMI effects not mediated by SBP, TC, HDL, or diabetes (supplemental Appendix Table 2). Optimistic sensitivity analyses simulated (1) an extremely aggressive tobacco control policy leading to an exponential decline in active smoking in Chinese men to 20% by 2020 and 10% by 2030 (supplemental Appendix Figure 3), (2) lowering mean SBP by 3.6 mm Hg in 2010 (SBP change associated with lowering mean dietary sodium 6 g/d),32 and (3) lowering case-fatality to recent US levels for CHD33 and stroke34 (supplemental Appendix Table 5). Pessimistic sensitivity analyses (1) repeated the high diabetes trend substituting stronger diabetes relative risk coefficients from Framingham, and (2) simulated a rise in TC by 2030 as high as the mean 6.0 mmol/L measured in 1960s US adults.18


Base Case and Trend Scenarios

China’s population ages 35 to 84 years is expected to grow from 0.67 billion in 2010 to 0.84 billion in 2030, and the proportion of persons ages ≥65 years in the total population will double (from 7% to 14%).35 In the baseline simulation with risk factors held at 2000 levels, 38.6 million CHD events and 129.8 million strokes were projected from 2010 to 2030 (Table 2). Approximately a quarter of all cardiovascular disease events were attributable to SBP >115 mm Hg, and TC >3.8 mmol/L (148 mg/dL) and smoking explained most of the remaining proportion of events that are attributable to the risk factors considered (Figure 1). Assuming constant age-specific event and case-fatality rates, annual CHD and stroke events will increase >50% between 2010 and 2030 and crude event rates will increase steadily due to aging and population growth alone (Figure 2A and 2B, Figure 3).

Table 2. Incremental Changes in Projected CHD and Stroke Events Attributable to Projected Trends in Cardiovascular Disease Risk Factors, Chinese Adults Ages 35 to 84 Years, 2010 to 2030, the CHD Policy Model–China

CHD EventsStroke EventsCHD EventsStroke Events
Base case 2010–2030
    Total24 255 00075 947 00014 339 00053 882 000
Trend cases: incremental events (% change from baseline)
        Main1 006 000 (4)6 571 000 (9)435 000 (3)4 769 000 (8)
        High1 332 000 (6)8 720 000 (12)590 000 (4)6 554 000 (12)
        Low−845 000 (−4)−6 300 000 (−8)−317 000 (−2)−3 668 000 (−7)
        Main3 800 000 (16)2 482 000 (3)1 169 000 (8)1 738 000 (3)
        High7 554 000 (31)4 658 000 (6)2 122 000 (15)3 084 000 (6)
        Low1 334 000 (6)907 000 (1)336 000 (2)509 000 (1)
    Active smoking
        Main−1 940 000 (−8)−586 000 (<−1)−105 000 (<−1)−37 000 (<−1)
        Worst−1 139 000 (−5)−869 000 (<−1)270 000 (2)86 000 (<1)
        Best−2 691 000 (−11)−379 000 (−1)−152 000 (−1)−135 000 (<−1)
        Main464 000 (2)1 608 000 (2)847 000 (5)726 000 (1)
        High740 000 (3)2 585 000 (3)1 411 000 (10)1 180 000 (2)
        Low108 000 (<1)366 000 (<1)190 000 (1)169 000 (<1)
        Mediated by SBP, TC, HDL, diabetes
            Main1 533 000 (6)3 665 000 (5)945 000 (7)1 650 000 (3)
            High2 545 000 (11)6 124 000 (8)1 469 000 (10)2 476 000 (5)
            Low960 000 (4)2 278 000 (3)647 000 (5)1 217 000 (2)
Simultaneous main trends SBP, TC, diabetes
    Smoking decline3 129 000 (13)10 153 000 (13)2 468 000 (17)7 269 000 (14)
    No smoking decline5 543 000 (23)10 806 000 (14)2 594 000 (18)7 307 000 (14)

Figure 1. Proportions of CHD, stroke, and cardiovascular disease events attributable to selected major risk factors in China, base case scenario 2010 to 2030.

Figure 2. A and B, Number of ischemic strokes, hemorrhagic strokes, and CHD events in Chinese men and women ages 35 to 84 years projected from the CHD Policy Model–China for the years 2010, 2015, 2020, 2025, and 2030. Dark blue areas represent events projected due to aging and population growth alone; red areas, additional events attributable to projected SBP, TC, diabetes, and smoking trends.

Figure 3. Crude event rates (per 100 000) of ischemic stroke, hemorrhagic stroke, and CHD in Chinese men and women ages 35 to 84 years projected for 2010, 2015, 2020, 2025, and 2030. Base case indicates risk factors held at year 2000 levels; risk factor trend case indicates main SBP, TC, diabetes, and smoking trends.

A TC increase of 0.58 mmol/L (22.4 mg/dL) in Chinese men and 0.55 mmol/L (21.6 mg/dL) in Chinese women over 2010 to 2030 (main assumption) would lead to the highest increase in CHD events of all risk factors modeled (Table 2). The main SBP trend (7.3 mm Hg increase in men, 8.4 mm Hg in women) would lead to the highest increase in stroke and combined cardiovascular disease—6.8 million incremental cardiovascular disease events in men, and 4.2 million in women, but a declining SBP trend (“low” scenario) would reduce events in almost equal proportion. Rising BMI was projected to increase CHD and stroke events 6% and 5% in men, and 7% and 3% in women, respectively, mediated through SBP, TC, diabetes, and HDL.

Main trends in SBP, TC, diabetes, and smoking combined would lead to an additional 13.2 million more cardiovascular disease events (13% increase) in Chinese men and an additional 9.7 million additional cardiovascular disease events (14% increase) in Chinese women over 2010 to 2030, despite a decreasing smoking trend. Though demographic trends would account for 68% of increases in annual cardiovascular disease 2010 to 2030, unfavorable cardiovascular disease risk factor trends would accelerate crude event rates (Figure 2A and 2B and Figure 3). The magnitude of the impact of the combined main trends in risk factors on event rates was greatest for ischemic stroke. Increased CHD in Chinese men from rising TC was blunted by concurrent decline in active smoking.

Projection of recent declines in active smoking in Chinese men would not counterbalance the cardiovascular consequences of increasing SBP, TC, diabetes, or BMI. However, a 0.6 percentage point annual decline in active smoking (main assumption) in Chinese men would prevent almost 1 million “noncardiovascular disease” deaths, such as cancer and chronic obstructive lung disease deaths. An increase in active smoking prevalence in women to 19% by the year 2030—the “worst case”—would lead to a <1% increase in CHD and stroke deaths, and an <1% increase in all-cause mortality over 2010 to 2030 because most of the substantial adverse effects would occur after 2030.

Sensitivity Analyses

When Framingham risk factor coefficients were substituted for the main CMCS coefficients, projected changes in CHD and stroke events varied according to differences in the strengths of the coefficients between the 2 studies (Figure 4A and 4B).

Figure 4. A and B, Sensitivity Analyses with CHD and total stroke risk coefficients estimated from Framingham Heart Study data substituted for China Multi-provincial Cohort Study (CMCS) coefficients, and main trend simulations repeated. Bars represent incremental percent change compared with the base case.

Assuming lower US case-fatality rates starting in 2010 would lower cardiovascular mortality in the base case by approximately 25% with a small increase in event rates due to more repeat events (Table 3, supplemental Appendix Table 7). Lower case-fatality would blunt cardiovascular mortality increases from projected trends in SBP, TC, and diabetes. When an aggressive lowering of smoking prevalence in men was simulated, avoided cardiovascular and noncardiovascular deaths were more than twice the main smoking trend simulation, and prevented noncardiovascular deaths would counterbalance cardiovascular death increases from unfavorable SBP, TC, diabetes, and BMI trends, leading to reduced male all-cause mortality. Lowering mean SBP 3.6 mm Hg in 2010 would be even more effective, lowering CHD, stroke, and noncardiovascular mortality in men and women. Blood pressure lowering would reduce cardiovascular and noncardiovascular mortality even if TC and diabetes increased and smoking prevalence stayed at the year 2000 level.

Table 3. Incremental Changes in Projected CHD and Stroke Events Projected With Optimistic and Pessimistic Scenarios for TC, SBP, Smoking, and Diabetes Assumptions, Chinese Adults Ages 35 to 84 Years, 2010 to 2030, the CHD Policy Model–China

CHD EventsStroke EventsCHD EventsStroke Events
*Main effect of lower case-fatality was approximately 25% decrease in CHD and stroke mortality (see Appendix Tables 7a and 7b).
†Incremental change compared with the lower case-fatality base case.
Base case 2010–2030 (totals)24 255 00075 947 00014 339 00053 882 000
Trend cases: incremental events [absolute and (%) change from main base case; except low case-fatality risk factor trend scenario compared with low case-fatality base case]
    Optimistic scenarios
        Base case with lower case-fatality starting 2010 (totals)*25 092 00077 008 00015 076 00054 608 000
        Main trends SBP, TC, diabetes+lower case-fatality starting 20103 230 000 (13)10 135 000 (13)2 711 000 (19)7 373 000 (14)
            Aggressive anti-tobacco policy−5 456 000 (−23)−1 679 000 (−2)
            SBP, TC, diabetes main trends+aggressive anti-tobacco−1 455 000 (−6)7 857 000 (10)
            Lower SBP 3.6 mm Hg−1 164 000 (−5)−7 253 000 (−10)−449 000 (−3)−4 658 000 (−9)
            TC, diabetes, smoking trends, lower SBP 3.6 mm Hg755 000 (3)−4 370 000 (−6)1 455 000 (10)−2 437,000 (−5)
            TC, diabetes, lower SBP 3.6 mm Hg, no smoking change2 963 000 (12)−3 824 000 (−5)1 575 000 (11)−2 401 000 (−5)
    Pessimistic scenarios
            Increase ceiling to 6.0 mmol/L11 649 000 (48)6 882 000 (9)3 417 000 (24)4 842 000 (9)
            Diabetes high trend and Framingham Heart Study diabetes β−coefficients3 285 000 (14)2 377 000 (3)1 903 000 (13)3 259 000 (6)
            Main (mediated by SBP, TC, HDL, diabetes)1 533 000 (6)3 665 000 (5)945 000 (7)1 650 000 (3)
            Additional nonmediated effects2 403 000 (10)3 379 000 (5)483 000 (3)2 426 000 (5)

Allowing TC mean to peak at 6.0 mmol/L by 2030 or assuming the diabetes high trend coupled with Framingham diabetes coefficients led to much larger projected increases in cardiovascular events. Simulating effects of BMI not mediated by SBP, TC, HDL, or diabetes increased projected cardiovascular disease events an additional 6% in men and 4% in women.


Even if risk factors stay at year 2000 levels, annual cardiovascular disease events in China probably will increase by more than a half between 2010 to 2030 due to aging and population growth. We forecast that projected cardiovascular risk factor trends will increase cardiovascular events by approximately an additional 14% in Chinese adults from 2010 to 2030, above and beyond demographic effects. The recent rate of decline in smoking will not be sufficient to counteract approximately 26 million cardiovascular disease events and nine million cardiovascular deaths added by deleterious trends in SBP, TC, diabetes, and BMI. We projected that an aggressive tobacco control policy—lowering active smoking prevalence to 20% by 2020 and 10% by 2030—would produce a reduction in total mortality in Chinese men despite adverse trends in other risk factors. Only lowering SBP across the adult population would reduce cardiovascular and noncardiovascular deaths in men and women.

We projected that unfavorable trends in SBP, TC, diabetes, and BMI would substantially augment cardiovascular disease event rates, and especially so for ischemic stroke. Chinese surveys have documented consumption of more dietary fats,1 overnutrition,36 and less physical activity3 over time. Additionally, relatively few Chinese adults with dyslipidemia,37 high blood pressure,38 or diabetes22 are aware of these risk factors. Zhao et al13 found a transition toward increased ischemic stroke and decreased hemorrhagic strokes in Beijing.38 In our model, less hemorrhagic stroke coupled with increased ischemic stroke occurred only if we simulated a modest SBP decline and large TC and diabetes increases. Because of the predominance of stroke in China and the strong association between blood pressure and stroke, optimistic blood pressure trend and intervention scenarios reduced cardiovascular and noncardiovascular outcomes most dramatically. If BMI has cardiovascular effects not mediated by SBP, total cholesterol, diabetes, HDL,39,40 or effects mediated by factors not modeled here,41 BMI would be on par with SBP and TC as a driver of adverse cardiovascular disease trends.

The Chinese government taxes tobacco products and has achieved a steady though slight decline in smoking. Only an extremely aggressive approach to tobacco control would prevent at least 4.5 million deaths from all causes in men from 2010 to 2030, and keep all-cause mortality from rising despite expected increased cardiovascular deaths. A stronger tobacco taxation policy could save millions of lives, and generate government revenues that would eclipse losses to industry and tobacco farmers.42

We assumed that increasing TC will increase CHD. CHD incidence declined in Japan despite a 0.5 mmol/L (20 mg/dL) mean rise in TC in adults between 1980 and 2000, presumably in part because SBP and smoking decreased, elevated cholesterol requires a long “incubation period,”43 or TC does not capture unique dietary influences or subfraction changes. Cardiovascular disease death rates usually decline with economic development, a trend slowed but not reversed by unfavorable cholesterol trends.44 We simulated 1 driver of decline in deaths with economic development by immediately improving case-fatality—lower case-fatality would lead to 25% fewer cardiovascular deaths in the base case and blunt cardiovascular mortality increases from unfavorable risk factor trends.

Assuming the higher diabetes prevalence or stronger diabetes coefficients resulted in two thirds to twice more the projected cardiovascular disease events compared with the main assumption fasting glucose-only diabetes definition of diabetes and CMCS diabetes coefficients. CMCS diabetes risk coefficients are weak compared with other studies,7,45 perhaps due to underdiagnosis or inclusion of predominantly mild cases of diabetes.

Prior Markov-style population models of cardiovascular disease in China used risk factor relative risks from Western and Asian cohort studies10,46 or China-specific risk equations.47 The accuracy of recalibrated Framingham prediction equations for Chinese populations remains controversial.6–8 Our simulations substituting Framingham coefficients for the CMCS coefficients yielded CHD and stroke projections that varied from the main projections by up to 16 percentage points. Stroke projections varied mostly because TC was not a significant predictor of total stroke in Framingham.48 Stroke predictions were more detailed and probably more accurate using China-specific stroke equations, but there was uncertainty regarding whether CMCS or Framingham CHD diabetes and cholesterol coefficients should be used.


Aging and growth of the Chinese population are certain, but the trends projected here were based on limited survey data gathered since China’s economic reforms after 1979 and remain uncertain. Much hinges on future rates of economic development and urbanization. HDL was not modeled (except as an indirect product of BMI), nor was widespread passive smoking exposure in Chinese women, both due to limited past survey data. Artificial ceilings limiting highest future risk factor levels may be overly conservative: on Nauru, diabetes prevalence already exceeds 30%,25 and total cholesterol was as high as 7.0 mmol/L in 1970s Finland.49 On the other hand, generalizing the rapid rise in total cholesterol observed in the urban Beijing population19 to all of China may have led to overestimation. For this analysis, for the sake of simplicity, uncertainty about trend projections was tested using only 1-way sensitivity analyses, which are limited compared with multiway analyses.


In this computer modeling study, unfavorable trends in SBP, TC, and diabetes from 2010 to 2030 were projected to increase cardiovascular disease events by approximately 14% above and beyond the increase expected due to aging and population growth, even if active cigarette smoking continues the recent rate of decline. Population-wide risk reduction policies, screening for cardiovascular disease risk factors, and scaling up of successful local risk factor prevention and treatment programs should be included in China’s health system reform. Even if other adverse risk factor trends continue unabated, national policy targeted toward aggressive tobacco control policy or blood pressure lowering could save 2.9 to 5.7 million lives during the next 20 years.

The online Data Supplement is available at

The authors thank the many investigators and participants who contributed to the surveys of cardiovascular risk factors in China over the years 1980 to 2008 reviewed. We particularly thank investigators and participants from the Chinese Multiprovincial Cohort Study for contributing the risk factor relative risks and the International Collaborative Study of Cardiovascular Disease in Asia Study and its participants for providing risk factor means and prevalence in China. We thank the China Health and Nutrition Survey and its participants, funded by NIH (R01-HD30880, DK056350, and R01-HD38700), and the Carolina Population Center and the Chinese Centers for Disease Control for providing the primary data for trends in blood pressure, BMI, and smoking. The Framingham Heart Study (FHS) and Framingham Offspring Study (FOS) are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the FHS and FOS Investigators. This article was prepared using a limited access dataset obtained by the NHLBI and does not necessarily reflect the opinions or views of the FHS, the FOS, or the NHLBI.

Sources of Funding

This study was supported by a grant from the Flight Attendants Medical Research Institute and a grant from the Swanson Family Fund to the University of California, San Francisco (to Dr Goldman), Mentored Career Development Award number K08HL089675 from the United States National Heart, Lung, and Blood Institute of the NIH, and a grant from the William J. Matheson Foundation to Columbia University (to Dr Moran).




Correspondence to Dongfeng Gu, Division of Population Genetics and Prevention, Cardiovascular Institute and Fu Wai Hospital, 167 Beilishi Rd, Beijing 100037, China (e-mail ) or Dong Zhao, MD, Beijing Institute of Heart, Lung, and Blood Vessel Diseases, Capital University of Medical Sciences affiliated with Beijing Anzhen Hospital, Chaoyang District, Beijing 100029 People’s Republic of China (e-mail [email protected]).


  • 1 Drewnowski A, Popkin BM. The nutrition transition: new trends in the global diet. Nutr Rev. 1997; 55: 31–43.MedlineGoogle Scholar
  • 2 Wang LD. Comprehensive report, Chinese nutrition and health survey in 2002. Beijing: People’s Medical Publishing House; 2005.Google Scholar
  • 3 Paeratakul S, Popkin BM, Keyou G, Adair LS, Stevens J. Changes in diet and physical activity affect the body mass index of Chinese adults. Int J Obes Relat Metab Disord. 1998; 22: 424–431.CrossrefMedlineGoogle Scholar
  • 4 Wildman RP, Gu D, Muntner P, Wu X, Reynolds K, Duan X, Chen CS, Huang G, Bazzano LA, He J. Trends in overweight and obesity in Chinese adults: between 1991 and 1999–2000. Obesity (Silver Spring, Md). 2008; 16: 1448–1453.CrossrefMedlineGoogle Scholar
  • 5 Gu D, Wu X, Reynolds K, Duan X, Xin X, Reynolds RF, Whelton PK, He J. Cigarette smoking and exposure to environmental tobacco smoke in China: the international collaborative study of cardiovascular disease in Asia. Am J Public Health. 2004; 94: 1972–1976.CrossrefMedlineGoogle Scholar
  • 6 Liu J, Hong Y, D'Agostino RB Sr, Wu Z, Wang W, Sun J, Wilson PW, Kannel WB, Zhao D. Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese Multi-Provincial Cohort Study. JAMA. 2004; 291: 2591–2599.CrossrefMedlineGoogle Scholar
  • 7 Wu Y, Liu X, Li X, Li Y, Zhao L, Chen Z, Li Y, Rao X, Zhou B, Detrano R, Liu K. Estimation of 10-year risk of fatal and nonfatal ischemic cardiovascular diseases in Chinese adults. Circulation. 2006; 114: 2217–2225.LinkGoogle Scholar
  • 8 Barzi F, Patel A, Gu D, Sritara P, Lam TH, Rodgers A, Woodward M. Cardiovascular risk prediction tools for populations in Asia. J Epidemiol Commun Health. 2007; 61: 115–121.CrossrefMedlineGoogle Scholar
  • 9 Leeder S, Raymond S, Greenberg H, Liu H, Esson K. Race Against Time: The Challenge of Cardiovascular Disease in Developing Countries. New York, NY: Columbia University Center for Global Health and Economic Development; 2004.Google Scholar
  • 10 Cheng J, Zhao D, Zeng Z, Critchley JA, Liu J, Wang W, Sun J, Capewell S. The impact of demographic and risk factor changes on coronary heart disease deaths in Beijing, 1999–2010. BMC Public Health. 2009; 9: 30.CrossrefMedlineGoogle Scholar
  • 11 Moran A, Zhao D, Gu D, Coxson P, Chen CS, Cheng J, Liu J, He J, Goldman L. The future impact of population growth and aging on coronary heart disease in China: projections from the coronary heart disease policy model-China. BMC Public Health. 2008; 8: 394.CrossrefMedlineGoogle Scholar
  • 12 He J, Neal B, Gu D, Suriyawongpaisal P, Xin X, Reynolds R, MacMahon S, Whelton PK. International collaborative study of cardiovascular disease in Asia: design, rationale, and preliminary results. Ethn Dis. 2004; 14: 260–268.MedlineGoogle Scholar
  • 13 Zhao D, Liu J, Wang W, Zeng Z, Cheng J, Liu J, Sun J, Wu Z. Epidemiological transition of stroke in China: twenty-one-year observational study from the Sino-MONICA-Beijing Project. Stroke. 2008; 39: 1668–1674.LinkGoogle Scholar
  • 14 Gu D, Kelly TN, Wu X, Chen J, Duan X, Huang JF, Chen JC, Whelton PK, He J. Blood pressure and risk of cardiovascular disease in Chinese men and women. Am J Hypertens. 2008; 21: 265–272.CrossrefMedlineGoogle Scholar
  • 15 He J, Gu D, Wu X, Reynolds K, Duan X, Yao C, Wang J, Chen CS, Chen J, Wildman RP, Klag MJ, Whelton PK. Major causes of death among men and women in China. N Engl J Med. 2005; 353: 1124–1134.CrossrefMedlineGoogle Scholar
  • 16 Stevens J, Truesdale KP, Katz EG, Cai J. Impact of body mass index on incident hypertension and diabetes in Chinese Asians, American Whites, and American Blacks: the People’s Republic of China Study and the Atherosclerosis Risk in Communities Study. Am J Epidemiol. 2008; 167: 1365–1374.CrossrefMedlineGoogle Scholar
  • 17 China Health and Nutrition Survey. [cited 2007 October 31]; Available at: Scholar
  • 18 Health, United States, 2008. [cited 2009 November 12]; Available at: Scholar
  • 19 Liu S, Zhao D, Wang W, Liu J, Qin L, Zeng Z, Wu Z. The trends of cardiovascular risk factors in urban and rural areas of Beijing during 1984–1999. J Cardiovasc Pulmon Dis. 2006; 25: 129–134.Google Scholar
  • 20 Li Z, Yang R, Xu G, Xia T. Serum lipid concentrations and prevalence of dyslipidemia in a large professional population in Beijing. Clin Chem. 2005; 51: 144–150.CrossrefMedlineGoogle Scholar
  • 21 World Health Organization. Global Infobase. [cited 2008 November]. Available at: Scholar
  • 22 Gu D, Reynolds K, Duan X, Xin X, Chen J, Wu X, Mo J, Whelton PK, He J. Prevalence of diabetes and impaired fasting glucose in the Chinese adult population: International Collaborative Study of Cardiovascular Disease in Asia (InterASIA). Diabetologia. 2003; 46: 1190–1198.CrossrefMedlineGoogle Scholar
  • 23 Pan XR, Yang WY, Li GW, Liu J. Prevalence of diabetes and its risk factors in China, 1994. National Diabetes Prevention and Control Cooperative Group. Diabetes Care. 1997; 20: 1664–1669.CrossrefMedlineGoogle Scholar
  • 24 Wang KLT, Xiang H. Study on the epidemiology characteristics of diabetes mellitus and IGT in China. Chin J Epidemiol. 1998; 19: 282–285.Google Scholar
  • 25 International Diabetes Federation. Diabetes Atlas. 2nd edition. [cited 2009 February]. Available at: Scholar
  • 26 Qiao Q, Hu G, Tuomilehto J, Nakagami T, Balkau B, Borch-Johnsen K, Ramachandran A, Mohan V, Iyer SR, Tominaga M, Kiyohara Y, Kato I, Okubo K, Nagai M, Shibazaki S, Yang Z, Tong Z, Fan Q, Wang B, Chew SK, Tan BY, Heng D, Emmanuel S, Tajima N, Iwamoto Y, Snehalatha C, Vijay V, Kapur A, Dong Y, Nan H, Gao W, Shi H, Fu F. Age- and sex-specific prevalence of diabetes and impaired glucose regulation in 11 Asian cohorts. Diabetes Care. 2003; 26: 1770–1780.CrossrefMedlineGoogle Scholar
  • 27 Wang Y, Beydoun MA. The obesity epidemic in the United States: gender, age, socioeconomic, racial/ethnic, and geographic characteristics: a systematic review and meta-regression analysis. Epidemiol Rev. 2007; 29: 6–28.CrossrefMedlineGoogle Scholar
  • 28 Ezzati M, Hoorn SV, Rodgers A, Lopez AD, Mathers CD, Murray CJ. Estimates of global and regional potential health gains from reducing multiple major risk factors. Lancet. 2003; 362: 271–280.CrossrefMedlineGoogle Scholar
  • 29 Gu D, He J, Duan X, Reynolds K, Wu X, Chen J, Huang G, Chen CS, Whelton PK. Body weight and mortality among men and women in China. JAMA. 2006; 295: 776–783.CrossrefMedlineGoogle Scholar
  • 30 Chen Z, Peto R, Collins R, MacMahon S, Lu J, Li W. Serum cholesterol concentration and coronary heart disease in population with low cholesterol concentrations. BMJ (Clin Res Ed). 1991; 303: 276–282.CrossrefMedlineGoogle Scholar
  • 31 Eastern Stroke and Coronary Heart Disease Collaborative Research Group. Blood pressure, cholesterol, and stroke in eastern Asia. Lancet. 1998; 352: 1801–1807.CrossrefMedlineGoogle Scholar
  • 32 He FJ, MacGregor GA. How far should salt intake be reduced? Hypertension. 2003; 42: 1093–1099.LinkGoogle Scholar
  • 33 Vaccarino V, Krumholz HM, Yarzebski J, Gore JM, Goldberg RJ. Sex differences in 2-year mortality after hospital discharge for myocardial infarction. Ann Intern Med. 2001; 134: 173–181.CrossrefMedlineGoogle Scholar
  • 34 Rosamond WD, Folsom AR, Chambless LE, Wang CH, McGovern PG, Howard G, Copper LS, Shahar E. Stroke incidence and survival among middle-aged adults: 9-year follow-up of the Atherosclerosis Risk in Communities (ARIC) cohort. Stroke. 1999; 30: 736–743.CrossrefMedlineGoogle Scholar
  • 35 International Database, US Census Bureau. 2006 [cited 2007 May 17]. Available at: Scholar
  • 36 Zhai F, Wang H, Wang Z, Popkin BM, Chen C. Closing the energy gap to prevent weight gain in China. Obes Rev. 2008; (Suppl 1): 107–112.MedlineGoogle Scholar
  • 37 He J, Gu D, Reynolds K, Wu X, Muntner P, Zhao J, Chen J, Liu D, Mo J, Whelton PK. Serum total and lipoprotein cholesterol levels and awareness, treatment, and control of hypercholesterolemia in China. Circulation. 2004; 110: 405–411.LinkGoogle Scholar
  • 38 Gu D, Reynolds K, Wu X, Chen J, Duan X, Muntner P, Huang G, Reynolds RF, Su S, Whelton PK, He J. Prevalence, awareness, treatment, and control of hypertension in china. Hypertension. 2002; 40: 920–927.LinkGoogle Scholar
  • 39 Davi G, Guagnano MT, Ciabattoni G, Basili S, Falco A, Marinopiccoli M, Nutini M, Sensi S, Patrono C. Platelet activation in obese women: role of inflammation and oxidant stress. JAMA. 2002; 288: 2008–2014.CrossrefMedlineGoogle Scholar
  • 40 Rosito GA, D'Agostino RB, Massaro J, Lipinska I, Mittleman MA, Sutherland P, Wilson PW, Levy D, Muller JE, Tofler GH. Association between obesity and a prothrombotic state: the Framingham Offspring Study. Thromb Haemost. 2004; 91: 683–689.CrossrefMedlineGoogle Scholar
  • 41 Koch R, Sharma AM. Obesity and cardiovascular hemodynamic function. Curr Hypertens Rep. 1999; 1: 127–130.CrossrefMedlineGoogle Scholar
  • 42 Hu TW, Mao Z. Effects of cigarette tax on cigarette consumption and the Chinese economy. Tob Control. 2002; 11: 105–108.CrossrefMedlineGoogle Scholar
  • 43 Iso H. Changes in coronary heart disease risk among Japanese. Circulation. 2008; 118: 2725–279.LinkGoogle Scholar
  • 44 Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med. 2006; 3: e442.CrossrefMedlineGoogle Scholar
  • 45 Lawes CM, Parag V, Bennett DA, Suh I, Lam TH, Whitlock G, Barzi F, Woodward M. Blood glucose and risk of cardiovascular disease in the Asia Pacific region. Diabetes Care. 2004; 27: 2836–2842.CrossrefMedlineGoogle Scholar
  • 46 Critchley J, Liu J, Zhao D, Wei W, Capewell S. Explaining the increase in coronary heart disease mortality in Beijing between 1984 and 1999. Circulation. 2004; 110: 1236–1244.LinkGoogle Scholar
  • 47 Qin X, Jackson R, Marshall R, Lee L, Cao W, Zhan S, Hu Y. Modelling the potential impact of population-wide and targeted high-risk blood pressure-lowering strategies on cardiovascular disease in China. Eur J Cardiovasc Prev Rehabil. 2009; 16: 96–101.CrossrefMedlineGoogle Scholar
  • 48 Wolf PA, D'Agostino RB, Belanger AJ, Kannel WB. Probability of stroke: a risk profile from the Framingham Study. Stroke. 1991; 22: 312–318.CrossrefMedlineGoogle Scholar
  • 49 Puska P, Tuomilehto J, Salonen J, Neittaanmaki L, Maki J, Virtamo J, Nissinen A, Koskela K, Takalo T. Changes in coronary risk factors during comprehensive five-year community programme to control cardiovascular diseases (North Karelia project). BMJ. 1979; 2: 1173–1178.CrossrefMedlineGoogle Scholar