Appendix:
Appendix A: Detailed description of the Coronary Heart Disease Policy Model-China:
The CHD Policy-China is a Markov (state-transition) model of cardiovascular disease in the adult Chinese population.(Moran et al. 2008) 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).(He et al. 2004) Age trends in risk factor levels were preserved over time. Stroke incidence,(Gu et al. 2008; Zhao et al. 2008) mortality,(He et al. 2005) and case-fatality (Zhao et al. 2008) estimates were derived from other Chinese studies. 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 and total (ischemic + hemorrhagic) stroke.
Model calibration: comparison with mortality rate targets for China
The CHD Policy Model-China defined CHD as myocardial infarction (ICD-9 410, 412 or ICD-10 I21, I22), angina and other CHD (ICD-9 411, 413 and 414, or IC-10 I20, I23-I25), and a fixed proportion of “ill-defined” cardiovascular disease coded events and deaths (ICD-9 codes 427.1, 427.4, 427.5, 428, 429.0, 429.1, 429.2, 429.9, 440.9 or ICD-10 I47.2, I49.0, I46, I50, I51.4, I51.5, I51.9, and I70.9).(Lozano 2001)
Stroke was defined by ICD-9 codes 430-438 (excluding transient ischemic attack) or ICD-10 I60-I69. Target total mortality for the Chinese adults aged 35-84 years in the year 2002 were obtained from the World Health Organization. Age and sex-specific CHD, stroke, and non-CVD mortality rates estimated from the Chinese National Hypertension Epidemiology Follow-up Survey (CHEFS) and then inflated rates by 30% to fit the ‘envelope’ of the WHO absolute mortality estimates. In a calibration procedure, incidence was adjusted to match with age- and sex-specific mortality targets within one percent. In order to evaluate the accuracy of CHD Policy Model predictions over time, China stroke and CHD mortality estimates for ages 35-84 years were obtained from the China Ministry of Health (MOH) and the World Health Organization (WHO). The figures below demonstrate that CHD Policy Model (CHDPM) predictions are reasonably close to MOH and WHO estimates over time, though the Model does not reproduce year-to-year fluctuations that may be artifactual.
Incidence of CHD and total stroke in persons with no prior diagnosis of cardiovascular disease
CHD incidence in men and women aged 35-84 years with no prior CHD diagnosis was based on 10-year incidence rates from the the China Hypertension Epidemiology Follow Up Study (CHEFS, Tables below).(Gu et al. 2008) and calibrated to fit with CHD mortality and case-fatality assumptions. Incident stroke rates were identified from the CHEFS.(Gu et al. 2008)
CHD and stroke case-fatality rate assumptions
Main CHD Policy Model-China 28-day case-fatality assumptions were estimated from pooled Beijing Sino-MONICA Study data from 1993-2004 (personal communication, Dong Zhao, MD, PhD, 2006) and the main age-specific CHD case-fatality rate assumptions were estimated from the overall rates (Tables below).
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Coronary Heart Disease (CHD) Inputs used for the CHD Policy Model-China
Sex/age / CHD incidence rate/100,000 / CHD 28 day case-fatality (proportion) / CHD Mortality/100,000Men
35-44 years
45-54
55-64
65-74
75-84 / 50
75
350
670
700 / 0.12
0.21
0.29
0.33
0.48 / 12
26
141
358
679
Women
35-44 years
45-54
55-64
65-74
75-84 / 20
40
170
420
550 / 0.18
0.23
0.27
0.43
0.51 / 5
17
74
236
449
Stroke Inputs used for the CHD Policy Model-China
Sex/age / Total strokeIncidence rate/100,000 / Total stroke 28 day case-fatality (proportion) / Total stroke Mortality/100,000Men
35-44 years
45-54
55-64
65-74
75-84 / 170
580
1,863
3,857
4,729 / 0.40
0.50
0.56
0.63
0.66 / 36
115
409
1120
1878
Women
35-44 years
45-54
55-64
65-74
75-84 / 152
355
1,153
2,244
3,443 / 0.40
0.40
0.50
0.62
0.65 / 34
72
255
706
1412
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Appendix B: Source of CHD and Stroke Incidence Estimates: Description of the China Hypertension Survey Epidemiology Follow Up Study (CHEFS):
Study Design: A multi-stage, random clustering design to was used to identify a nationally-representative sample of Chinese men and women >= age 15 years beginning in 1991 living in all of China’s 30 provinces. In 1999, investitgators from each province were invited to participate in a the China National Hypertension Survey Follow Up Study (CHEFS).(He et al. 2005; Kelly et al. 2008) Seventeen provinces participated in the follow up study (Appendix Figure 1). 83,533 men and 86,338 women older than age 40 at the time of the 1991 baseline examination were eligible for follow-up. Follow up disease event data were gathered from 158,666 participants or proxies by interview in 1999-2000 (93.4 percent follow-up rate). Urban and rural status was determined according to China census designations, and North and South China were divided by the Yangtze river.
Appendix Figure 1. Map of China with provinces participating in the China Hypertension Survey Follow Up Study, 1991-2000. Reprinted from Kelly et al., Circulation. 2008.(Kelly et al. 2008)
Follow up and ascertainment of cardiovascular disease events: In follow up examinations during 1999 and 2000, participants or their proxies were tracked to a current address and in-depth interviews were conducted in order to obtain information on history of disease, hospitalizations, or deaths. For deaths, death certificates were obtained from local public health or police departments. For hospitalized deaths, hospital records were obtained, including physical examination, laboratory findings, electrocardiograph records, brain imaging, and autopsy findings were included in the evaluation of cases. An end-point assessment committee in each province reviewed and confirmed (or rejected the hospital discharge diagnosis or cause of death on the basis of abstracted information, using prespecified criteria. A study-wide endpoint assessment committee at the Chinese Academy of Medical Sciences in Beijing, consisting of cardiologists, neurologists, and a clinical epidemiologist reviewed all diagnostic and cause of death information and determined the final diagnosis or cause of death. Two committee members independently verified diagnosis or cause of death and disagreements were adjudicated after discussion by other committee members. Cases were also classified according to the International Classification of Diseases, Ninth Revision (ICD-9). For this analysis, strokes were defined by ICD-9 codes 430-438. Coronary Heart Disease events were defined as myocardial infarction (ICD-9 410, 412 or ICD-10 I21, I22), angina and other CHD (ICD-9 411, 413 and 414, or IC-10 I20, I23–I25), and a fixed proportion of "ill-defined" cardiovascular disease coded events and deaths (ICD-9 codes 427.1, 427.4, 427.5, 428, 429.0, 429.1, 429.2, 429.9, 440.9 or ICD-10 I47.2, I49.0, I46, I50, I51.4, I51.5, I51.9, and I70.9).(Lozano 2001; Moran et al. 2010; Moran et al. 2008).
Appendix C: Rural and urban age structure assumptions
Different age structures were assumed for urban and rural China, which captures the higher rates of migration in younger adults. The result is that China will have a higher proportion of elderly adults in rural areas and a higher proportion of young adults in urban areas. The table below shows the assumed age structures for urban and rural China in 2030.
Age structure template: U.N., urban, 2030Sex / 35-39 / 40-44 / 45-49 / 50-54 / 55-59 / 60-64 / 65-69 / 70-74 / 75-79 / 80+
males / 0.0639 / 0.0707 / 0.0580 / 0.0522 / 0.0657 / 0.0648 / 0.0461 / 0.0345 / 0.0270 / 0.0188
urban / 0.0696 / 0.0771 / 0.0575 / 0.0494 / 0.0602 / 0.0610 / 0.0435 / 0.0317 / 0.0236 / 0.0165
rural / 0.0581 / 0.0644 / 0.0584 / 0.0549 / 0.0712 / 0.0687 / 0.0487 / 0.0372 / 0.0304 / 0.0211
check / 0.0639 / 0.0707 / 0.0580 / 0.0522 / 0.0657 / 0.0648 / 0.0461 / 0.0345 / 0.0270 / 0.0188
females / 0.0557 / 0.0651 / 0.0555 / 0.0507 / 0.0652 / 0.0644 / 0.0475 / 0.0365 / 0.0310 / 0.0269
urban / 0.0591 / 0.0704 / 0.0554 / 0.0489 / 0.0625 / 0.0639 / 0.0449 / 0.0323 / 0.0264 / 0.0234
rural / 0.0524 / 0.0599 / 0.0557 / 0.0526 / 0.0678 / 0.0649 / 0.0500 / 0.0406 / 0.0355 / 0.0303
check / 0.0557 / 0.0651 / 0.0555 / 0.0507 / 0.0652 / 0.0644 / 0.0475 / 0.0365 / 0.0310 / 0.0269
The UN age structure in 2030 already takes into account the effect of aging, not the effect of migration b/c is at the country level. Because 2005 was the most recent year for which the UN reported urban and rural age structures, the UN 2005 age structures for urban and rural China were used for the 2030 projections (the was added more explicitly (Methods top of page 5). We were concerned that using the 2005 age structures for urban and rural underestimates the effect of intense rural-urban migration over time. However, in the end, our 2030 age structure is similar to the age structure for urban and rural China in 2030 presented in Cao et al. 2012(Cao 2012):
Rural population (please note that we have proportions and Cao presents absolute numbers)
From Cao et al. 2012
From our data
Urban population
From Cao et al. 2012
From our data
Appendix Table1. Age-Standardized prevalence of cardiovascular diseaserisk factors in China stratified by gender, north or south China, and urban/rural status, the International Collaborative Study of Cardiovascular Disease in Asia Study (InterASIA), 2000-2001. Adapted with permission from Gu et al., 2005.(Gu et al. 2005)
Population Group / Dyslipidemia* / Hypertension† / Diabetes‡ / Current Smoking / Overweight§Total / 53.6 (0.6) / 26.1 (0.5) / 5.2 (0.2) / 34.4 (0.5) / 28.2 (0.5)
Men
Overall / 53.8 (0.8) / 27.6 (0.7) / 4.9 (0.3) / 60.6 (0.8) / 26.1 (0.7)
Regions
North / 61.2 (1.1) / 35.8 (1.1) / 5.2 (0.5) / 59.1 (1.1) / 41.4 (1.1)
South / 48.6 (1.1) / 21.9 (0.9) / 4.8 (0.4) / 61.6 (1.0) / 15.6 (0.7)
Urban / 67.3 (0.9) / 30.9 (0.9) / 7.4 (0.5) / 54.9 (0.9) / 40.8 (0.9)
Rural / 50.4 (1.0) / 26.8 (0.8) / 4.3 (0.4) / 62.0 (0.9) / 22.4 (0.8)
Women
Overall / 53.4 (0.8) / 24.6 (0.6) / 5.4 (0.3) / 6.8 (0.4) / 30.5 (0.7)
Regions
North / 59.8 (1.1) / 30.1 (1.0) / 6.8 (0.5) / 5.3 (0.5) / 45.0 (1.1)
South / 49.0 (1.0) / 20.8 (0.8) / 4.5 (0.4) / 7.9 (0.6) / 20.1 (0.8)
Urban / 58.7 (0.9) / 24.9 (0.7) / 7.1 (0.5) / 3.4 (0.3) / 38.8 (0.9)
Rural / 52.1 (0.9) / 24.6 (0.8) / 5.0 (0.4) / 7.7 (0.5) / 28.4 (0.8)
*Total cholesterol ≥5.2 mmol/L, HDL cholesterol <1.0 mmol/L, serum triglycerides ≥1.7 mmol/L, LDL cholesterol ≥3.4 mmol/L, and/or current cholesterol-lowering medication use.
†SBP ≥140 mm Hg and/or DBP ≥90 mm Hg and/or current antihypertensive medication use.
‡Fasting plasma glucose ≥7.0 mmol/L and/or current antidiabetes medication use.
§Body mass index ≥25 kg/m2.
SE indicates standard error.
Appendix Table 2. Risk factor changes between 2000 and 2030 assumed for the comparative analysis of projected risk factor trends from an earlier analysis (Moran et al. 2010), and the results of the urbanization trend analysis (manuscript Table 2). 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.
Main risk factor trend / Trend source / Trend function / Year 2000M= males
F= femles / Year 2030 (projected)
SBP (mean, mmHg) / China Health and Nutrition Surveys* / Linear / M 126.7
F 124.9 / M 134.0
F 133.2
Total cholesterol
(mean, mmol/l) / Sino-MONICA, Beijing† / Logistic / M 4.7
F 4.8 / M 5.3
F 5.4
Smoking (%) / China Health and Nutrition Surveys / Linear / M 59.8
F 7.1 / M 36.6
F 1.9
Diabetes (%) / National surveys¶§‡ / Logistic / M 5.3
F 6.1 / M 14.8
F 15.8
BMI (mean, kg/m²) / China Health and Nutrition Surveys / Linear / M 23.1
F 23.5 / M 26.4
F 26.4
*China Health and Nutrition Survey. Carolina Population Center, University of North Carolina.
†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 CardiovascPulmon Dis. 2006;25:129 –134.
¶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 CardiovascularDisease in Asia (InterASIA). Diabetologia. 2003;46:1190 –1198.
§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.
‡Wang KLT, Xiang H. Study on the epidemiology characteristics of diabetes mellitus and IGT in China.Chin J Epidemiol. 1998;19:282–285.
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