|Home | About | Journals | Submit | Contact Us | Français|
The relative effects of individual and combined risk factor trends on future cardiovascular disease in China have not been quantified in detail.
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.
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-1980’s, 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 China9–10 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.
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 ten-year age categories ages 35–84 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-fatality 13 estimates were derived from other Chinese studies (Appendix Table 1).. Multivariate CHD and ischemic stroke hazard ratios for age, sex, 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, Appendix Table 2).6 Cox proportional hazard models for hemorrhagic stroke (same risk factors excepting cholesterol, BMI, and diabetes) and non-cardiovascular 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 non-cardiovascular 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 one 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 one 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 non-cardiovascular deaths (total mortality – stroke and CHD mortality) are reported in Appendix tables. “Cardiovascular disease” was defined as combined CHD, ischemic stroke, and hemorrhagic stroke.
Based on secular trends in SBP, TC, active smoking, BMI, and diabetes analyzed from 1980–2006 (Appendix Tables 3 and 4, Appendix Figure 1) future risk factor trends for the population aged 35–84 years were projected forward over 2010–2030 (Table 1, Appendix Figures 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 1991–2006 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 pre-determined 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, TX) and Excel (Microsoft, Redmond, WA).
The CHD Policy Model-China simulated effects of projected risk factor trends on cardiovascular disease over 2010–2030. A base case simulated cardiovascular disease events over 2010—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 (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.
One-way sensitivity analyses explored uncertainty about main analysis trend projections and potential benefits of controlling smoking or SBP. Risk factor beta coefficients estimated from Framingham Heart Study data (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 (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 (Appendix Figure 3), 2) lowering mean SBP by 3.6 mmHg in 2010 (SBP change associated with lowering mean dietary sodium 6 g/day),32 and 3) lowering case-fatality to recent U.S. levels for CHD33 and stroke34 (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 1960’s U.S. adults.18
China’s population aged 35–84 years is expected to grow from 0.67 billion in 2010 to 0.84 billion in 2030, and the proportion of person aged ≥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 2010–2030 (Table 2). Approximately a quarter of all cardiovascular disease events were attributable to SBP >115 mmHg, 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 (Figures 2a and 2b, Figure 3).
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 2010–2030 (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 2010–2030, despite a decreasing smoking trend. Though demographic trends would account for 68% of increases in annual cardiovascular disease 2010–2030, unfavorable cardiovascular disease risk factor trends would accelerate crude event rates (Figures 2a and 2b, 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 one million “non-cardiovascular 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 2010–2030 because most of the substantial adverse effects would occur after 2030.
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 two studies (Figures 4a, 4b).
Assuming lower U.S. 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, 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 non-cardiovascular deaths were more than twice the main smoking trend simulation, and prevented non-cardiovascular 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 mmHg in 2010 would be even more effective, lowering CHD, stroke, and non-cardiovascular mortality in men and women. Blood pressure lowering would reduce cardiovascular and non-cardiovascular mortality even if TC and diabetes increased and smoking prevalence stayed at the year 2000 level.
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, cardiovascular disease events in China will likely increase by more than a half between 2010–2030 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 2010–2030, 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 non-cardiovascular 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 pressure38 or diabetes22 are aware of these risk factors. Zhao et al. found a transition toward increased ischemic stroke and decreased hemorrhagic strokes in Beijing.39 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 non-cardiovascular outcomes most dramatically. If BMI has cardiovascular effects not mediated by SBP, total cholesterol, HDL40–41 or effects mediated by factors not modeled here,42 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.43
We assumed 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’, 44 or TC does not capture unique dietary influences or sub-fraction changes. Cardiovascular disease death rates usually decline with economic development, a trend slowed, but not reversed by unfavorable cholesterol trends.45 We simulated one 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, 46 perhaps due to under-diagnosis 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, 47 or China-specific risk equations.48 The accuracy of re-calibrated 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.49 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 1970’s Finland.50 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 one-way sensitivity analyses, which are limited compared with multi-way analyses.
In this computer modeling study, unfavorable trends in SBP, TC, and diabetes from 2010–2030 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 2.9–5.7 million lives during the next 20 years.
The authors are greatly indebted to the many investigators and participants who contributed to the surveys of cardiovascular risk factors in China over the years 1980–2008 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 manuscript 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: 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 LG), and 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 AM)
Disclosures: The authors have no conflict of interest to report.