Background: In recent years, stroke has become the leading cause of death in the Chinese population, and the burden of stroke is huge. The aim of this study was to describe the epidemiological characteristics of population-based stroke incidence and case fatality rates in China, which are nationally representative. Methods: In 2013, a nationally representative household survey was conducted at 155 survey sites in 31 provinces. All stroke cases occurring within 1 year before the start of the survey period, including first-ever and recurrent strokes, were considered event cases. According to computed tomography, magnetic resonance imaging, and autopsy results, stroke was classified as ischemic, hemorrhagic, subarachnoid hemorrhagic, or difficult-to-classify stroke. The 7- and 30-day case fatality rates after stroke onset were investigated. Results: A total of 595,711 people were surveyed, with 2,164 diagnosed stroke events and 1,645 first-ever strokes. The age-standardized incidence of first-ever stroke and stroke event incidence in the Chinese population were 229.5 and 300.61 per 100,000 person-years, respectively. The world population age-standardized incidence of first-ever stroke and stroke events by the World Health Organization were 188.5 and 246.3 per 100,000 person-years, respectively. Among the 31 provinces, the top five incidence rates of first-ever stroke were recorded in Shaanxi, Heilongjiang, Ningxia, Henan, and Tianjin (518.0, 400.8, 389.5, 366.6, and 344.0 per 100,000 person-years, respectively). The top five incidence rates of stroke events were documented in Heilongjiang, Shaanxi, Henan, Tianjin, and Ningxia (672.7, 603.1, 580.2, 469.0, and 456.2 per 100,000 person-years, respectively). The 7- and 30-day case fatality rates were 14.3% and 17.8% for patients with first-ever stroke, respectively. Significant differences in the 30-day mortality rate of different stroke subtypes were recorded: 8.3% (95% confidence interval [CI], 8.2–8.5) for ischemic stroke, 44.4% (95% CI, 42.2–46.5) for cerebral hemorrhage, and 3.1% (95% CI, 3.0–3.3) for subarachnoid hemorrhage (p < 0.0001). Compared with the area of residence, the 30-day mortality rate of first-ever stroke in rural areas was 19.8% (95% CI, 19.3–20.3), which was higher than that in urban areas (14.9% [95% CI, 14.5–15.3]) (p = 0.011). Conclusion: In China, the incidences of first-ever stroke and stroke events are increasing, whereas the early case fatality rate is declining, which will inevitably lead to a higher stroke prevalence and a greater stroke burden. Therefore, the primary and secondary prevention strategies should be strengthened to reduce the incidence and burden of stroke.

Stroke is the second leading cause of death worldwide in people aged ≥60 years and the fifth leading cause of death in people aged 15–59 years [1]. In recent years, cerebrovascular disease has become the first cause of death in Chinese population [2] and is the main cause of long-term disability in adults, and its high incidence, disability, and mortality have become a global public health problem [3]. To identify the true burden and epidemiological factors of stroke, the National Epidemiological Survey of Stroke in China (NESS-China) was conducted in 2012–2013 [4]. The incidence of first-ever stroke, prevalence, and mortality in adults aged ≥20 years across all major regions in China have been reported [4, 5]. Recurrent strokes account for one-quarter of the stroke burden [6], and they can increase the risk of dementia, depression, and anxiety [7‒9], further increasing the patient, family, and healthcare burden. However, only a few studies have reported the population-based incidence of stroke events and case fatality rate, including first-ever stroke and stroke recurrence, in recent years in China. Several previous studies have focused on screening or intervention on stroke prevention, and they lacked national representativeness and were not well-designed epidemiological surveys [10, 11]. Furthermore, some published stroke case fatalities are inconsistent between and within regions, which may be due to selected samples that are not representative of the general population in China or due to differences in diagnosis, analysis, or design methods [12]. These epidemiological data are important for developing stroke prevention and control strategies. The NESS-China study overcame the above limitations of previous studies as much as possible. First, the NESS-China study is the first nationally representative stroke epidemiological survey, and it included all the 31 provinces in mainland China. Second, the survey used the uniform diagnostic criteria consistent with international standards. Third, neurologists were involved in the survey, which ensured the accuracy of the diagnosis [4]. Therefore, data from the NESS database were further sorted and mined to obtain stroke-related data, namely, the incidence of first-ever stroke, stroke events, and early case fatality rate in China.

Sample Population Distribution and Study Design

The NESS-China study was conducted on the National Disease Surveillance Points (DSP) System, which is representative in the national population age and sex, social and economic status, and geographical distribution in China. The methodology, including study design, sample size calculations, diagnostic criteria, and data collection, is described in detail in a published article [4]. The NESS-China study was conducted from September 1, 2013, to December 31, 2013, at 155 sites. Our survey included all the 31 provinces in mainland China. The 31 provincial regions included 4 municipalities (Beijing, Shanghai, Tianjin, and Chongqing), five autonomous regions (Inner Mongolia, Ningxia, Xinjiang, Tibet, and Guangxi), and 22 provinces. The multistage, stratified clustering sampling technique was used to select the individuals. We defined all the survey districts in rural survey sites (engaged in agricultural labor) as the rural regions and in cities (large, middle, or small cities) as the urban regions. In the stage of sampling, first, one town/district proportional to the population size of that area was selected in each survey sites. Second, in each selected location, one or more urban communities/villages with a total population of at least 4,500 residents (approximately 1,500 households) were selected by using the random sampling method [4]. All the respondents had lived in the county (or district) for at least 6 months before the survey commenced. The study was designed by the Center for Disease Control and Prevention investigators and neurologists as a door-to-door survey. The incidence of stroke was calculated using cases between September 1, 2012 and August 31, 2013.

Training and Quality Control

To ensure that each investigator has a consistent grasp of the survey standards and implements them during the investigation and that the data obtained are authentic and reliable, the survey employed a strict training and quality control process. First, all participants received rigorous training before the survey commenced, including national and provincial training. Second, after the training, the participants were assessed, and those who passed the assessment were considered for the investigation. Third, quality control measures were employed in the on-site investigation, data recovery, and data collation stages of the investigation and implementation process. Finally, dedicated quality control teams for both national and provincial project teams implemented various quality control measures.

Diagnostic Criteria and Definition

We defined stroke as “rapidly developing clinical signs of focal (or global) disturbance of cerebral function, lasting more than 24 h or leading to death, with no apparent cause other than that of vascular origin” based on the World Health Organization (WHO) guidelines [13]. Stroke diagnosis must exclude neurological disorders caused by trauma, tumors, metabolic, toxic, or central nervous system infections. According to the epidemiological diagnostic criteria used in the survey, stroke was classified as four main types: (1) ischemic stroke (IS), (2) intracerebral hemorrhage (ICH), (3) subarachnoid hemorrhage (SAH), and (4) stroke of undefined pathological type (UND). According to the MONICA study, the criterion for the incidence of stroke events is 28 days, multiple episodes within 28 days are considered one onset event, and recurrence after 28 days is recorded as another new-onset event [14]. All first-ever incident and recurrent strokes were calculated as stroke events. The 7- and 30-day case fatality rates were defined as the proportion of the included patients who died within 7 or 30 days after stroke onset.

Data Collection

Initially, preliminary screening was conducted by the Center for Disease Control and Prevention investigators. A total of 595,711 participants were included in the NESS-China study. During the preliminary screening phase, all participants information, including the basic information (gender, age, educational level, marital status, etc.), medical history information (previous medical history and related symptoms screening), and information on the death of family members since 1 September 2012 (cause of death, time of death, cerebrovascular disease before death, etc.), were collected. In order to obtain accurate data on stroke incidence, it is important to understand the circumstances of death after stroke onset. Information about stroke death was retrospectively obtained in 2 manners, including the survey and information from the DSP system. The two approaches complemented and corroborated each other. After the preliminary phase, all survival respondents with suspected stroke symptoms or a history of stroke/transient ischemic attack were invited for further consultation with a neurologist. At the same time, neurologists should also interview the family members of the deceased who are suspected or confirmed to have died of cerebrovascular disease or who suffered from cerebrovascular disease before death. At this stage, neurologists interviewed 28,506 participants and completed the information collection. All stroke cases were divided into first-ever stroke and recurrent stroke events.

Statistical Analyses

The demographic profiles of the study participants are delineated with frequencies (%) for categorical variables and means ± standard deviations for continuous variables, encompassing the entire population and stratified by sex, residential status (urban/rural), age, and socioeconomic standing. The incidence of first-ever stroke (per 100,000 individuals) and the rate of stroke event occurrences (per 100,000 individuals per year) were ascertained, categorized by age and sex. Both crude and age-standardized incidence rates, employing the direct method of standardization with the China Census 2010 and the WHO world standard population as references, were computed alongside their 95% confidence intervals (CIs; calculated using a two-sided approach at u = 1.96) based on the Poisson distribution. Descriptive statistics were utilized to evaluate disparities between genders: variations in the distribution of categorical variables were examined through the Cochran-Armitage trend test. All statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA).

The participant characteristics are shown in Table 1. The total number of respondents was 595,711, and more than one-third of 245,192 (41.2%) had only primary education or lower. Moreover, 65.7% were married. The majority were farmers (45.5%). The sociolect and demographic characteristics of the study participants were consistent with those of China as a whole. Among the 595,711 study participants, 1,645 first-ever strokes (54.9% in men) and 2,164 stroke events (55.5% in men) were recorded for 12 months. Sixty-nine patients had two stroke events, and eight had three stroke events during the surveyed year. The first-ever strokes included 1,145 (69.6%) cerebral infarction, 392 (23.8%) ICH, 73 (4.4%) SAH, and 35 (2.1%) UND. Moreover, stroke events including first-ever and recurrent strokes were identified, of which IS accounted for 1,573 (72.7%); ICH, 460 (21.2%); SAH, 89 (4.1%); and UND, 42 (1.9%) (Table 2). The proportions were roughly comparable.

Table 1.

Characteristics of the study participants

CharacteristicsOverall, n (%)Men, n (%)Women, n (%)p value
Participants 595,711 (100) 299,725 (50.3) 295,986 (49.7)  
Residence (urban) 282,169 (47.4) 139,699 (46.6) 142,470 (48.1) <0.0001 
Age groups    <0.0001 
 0–34 257,260 (43.2) 131,538 (43.9) 125,722 (42.5)  
 35–44 103,269 (17.3) 52,685 (17.6) 50,584 (17.1)  
 45–54 90,793 (15.2) 45,367 (15.1) 45,426 (15.4)  
 55–64 77,519 (13.0) 37,875 (12.6) 39,644 (13.4)  
 65–74 42,929 (7.2) 21,120 (7.1) 21,809 (7.4)  
 75–84 20,325 (3.4) 9,643 (3.2) 10,682 (3.6)  
 >85 3,616 (0.6) 1,497 (0.5) 2,119 (0.7)  
Education    <0.0001 
 Primary or lower 245,192 (41.2) 113,809 (38.0) 131,383 (44.4)  
 Middle school 294,193 (49.4) 156,467 (52.2) 137,726 (46.5)  
 College or higher 51,721 (8.7) 26,882 (9.0) 24,839 (8.4)  
 Missing 4,605 (0.8) 2,567 (0.9) 2,038 (0.7)  
Marital status    <0.0001 
 Married 391,124 (65.7) 193,599 (64.6) 197,525 (66.7)  
 Single 115,438 (19.4) 65,187 (21.8) 50,251 (17.0)  
 Widowed 32,731 (5.5) 11,234 (3.8) 21,497 (7.3)  
 Other 50,525 (8.5) 26,501 (8.8) 24,024 (8.1)  
 Missing 5,893 (1.0) 3,204 (1.1) 2,689 (0.9)  
Occupation    <0.0001 
 Students or preschool 105,510 (17.7) 55,132 (18.4) 50,378 (17.0)  
 Worker 45,004 (7.6) 25,749 (8.6) 19,255 (6.5)  
 Farmer 270,916 (45.5) 136,044 (45.4) 134,872 (45.6)  
 Employee 46,075 (7.7) 25,052 (8.4) 21,023 (7.1)  
 Entrepreneurs 21,323 (3.6) 11,250 (3.8) 10,073 (3.4)  
 Retired or unemployed 49,142 (8.3) 22,182 (7.4) 26,960 (9.1)  
 Other 48,795 (8.2) 19,243 (6.4) 29,552 (10.0)  
 Missing 8,946 (1.5) 5,073 (1.7) 3,873 (1.3)  
CharacteristicsOverall, n (%)Men, n (%)Women, n (%)p value
Participants 595,711 (100) 299,725 (50.3) 295,986 (49.7)  
Residence (urban) 282,169 (47.4) 139,699 (46.6) 142,470 (48.1) <0.0001 
Age groups    <0.0001 
 0–34 257,260 (43.2) 131,538 (43.9) 125,722 (42.5)  
 35–44 103,269 (17.3) 52,685 (17.6) 50,584 (17.1)  
 45–54 90,793 (15.2) 45,367 (15.1) 45,426 (15.4)  
 55–64 77,519 (13.0) 37,875 (12.6) 39,644 (13.4)  
 65–74 42,929 (7.2) 21,120 (7.1) 21,809 (7.4)  
 75–84 20,325 (3.4) 9,643 (3.2) 10,682 (3.6)  
 >85 3,616 (0.6) 1,497 (0.5) 2,119 (0.7)  
Education    <0.0001 
 Primary or lower 245,192 (41.2) 113,809 (38.0) 131,383 (44.4)  
 Middle school 294,193 (49.4) 156,467 (52.2) 137,726 (46.5)  
 College or higher 51,721 (8.7) 26,882 (9.0) 24,839 (8.4)  
 Missing 4,605 (0.8) 2,567 (0.9) 2,038 (0.7)  
Marital status    <0.0001 
 Married 391,124 (65.7) 193,599 (64.6) 197,525 (66.7)  
 Single 115,438 (19.4) 65,187 (21.8) 50,251 (17.0)  
 Widowed 32,731 (5.5) 11,234 (3.8) 21,497 (7.3)  
 Other 50,525 (8.5) 26,501 (8.8) 24,024 (8.1)  
 Missing 5,893 (1.0) 3,204 (1.1) 2,689 (0.9)  
Occupation    <0.0001 
 Students or preschool 105,510 (17.7) 55,132 (18.4) 50,378 (17.0)  
 Worker 45,004 (7.6) 25,749 (8.6) 19,255 (6.5)  
 Farmer 270,916 (45.5) 136,044 (45.4) 134,872 (45.6)  
 Employee 46,075 (7.7) 25,052 (8.4) 21,023 (7.1)  
 Entrepreneurs 21,323 (3.6) 11,250 (3.8) 10,073 (3.4)  
 Retired or unemployed 49,142 (8.3) 22,182 (7.4) 26,960 (9.1)  
 Other 48,795 (8.2) 19,243 (6.4) 29,552 (10.0)  
 Missing 8,946 (1.5) 5,073 (1.7) 3,873 (1.3)  

The overall crude incidence rates of first-ever stroke and stroke events were 276.1 (95% CI, 262.8–289.5) per 100,000 person-years and 363.3 (95% CI, 348.0–378.5) per 100,000 person-years, respectively (Table 2). When normalized using the 2010 Chinese population, the overall incidences of first-ever stroke and stroke events were 229.5 (95% CI, 217.3–241.6) and 300.6 (95% CI, 286.7–314.5) per 100,000 person-years. When normalized using the WHO world population, the overall incidence of first-ever stroke was 188.5 (95% CI, 177.5–199.5) per 100,000 person-years, and the overall incidence of stroke events was 246.3 (95% CI, 233.7–258.8) per 100,000 person-years.

Table 2.

Age-standardized incidence rates (with 95% CI) of stroke per 100,000 person-year of Chinese people by age and stroke pathological types

ISICHSAHUNDTotal
first-ever strokestroke eventsfirst-ever strokestroke eventsfirst-ever strokestroke eventsfirst-ever strokestroke eventsfirst-ever strokestroke events
Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)
0–34 8.5 (1.9–18.1) 9.6 (2.1–20.4) 6.4 (1.4–13.6) 7.5 (1.6–15.9) 0 (0–0) 0 (0–0) 0 (0–0) 0 (0–0) 14 5.4 (2.6–8.3) 16 6.2 (3.2–9.3) 
35–44 33 36.6 (20.7–52.8) 39 43.3 (24.4–62.4) 19 21.1 (11.9–30.4) 23 25.5 (14.4–36.8) 2.2 (1.3–3.2) 2.2 (1.3–3.2) 0 (0–0) 0 (0–0) 54 52.3 (38.3–66.2) 64 62 (46.8–77.2) 
45–54 146 131.4 (108.7–153.9) 186 167.4 (138.6–196.2) 59 53.1 (43.9–62.2) 71 63.9 (52.9–74.9) 12 10.8 (8.9–12.6) 13 11.7 (9.7–13.7) 5.4 (4.5–6.3) 7.2 (6.0–8.4) 223 245.6 (213.4–277.8) 278 306.2 (270.3–342.1) 
55–64 340 429.3 (384–474.7) 474 598.5 (535.4–661.8) 96 121.2 (108.4–134) 113 142.7 (127.6–157.8) 21 26.5 (23.7–29.3) 26 32.8 (29.4–36.3) 11.4 (10.2–12.6) 12 15.2 (13.6–16.8) 466 601.1 (546.7–655.6) 625 806.3 (743.3–869.2) 
65–74 346 582.4 (531–633.9) 511 860.1 (784.2–936.1) 90 151.5 (138.1–164.9) 109 183.5 (167.3–199.7) 20 33.7 (30.7–36.6) 27 45.4 (41.4–49.5) 10.1 (9.2–11) 11.8 (10.7–12.8) 462 1,076.2 (978.6–1,173.8) 654 1,523.4 (1,407.6–1,639.3) 
75–84 225 696.6 (631.7–761.6) 297 919.6 (833.9–1,005.3) 85 263.2 (238.6–287.7) 95 294.1 (266.7–321.6) 15 46.4 (42.1–50.8) 18 55.7 (50.5–60.9) 11 34.1 (30.9–37.2) 12 37.2 (33.7–40.6) 336 1,653.1 (1,477.8–1,828.4) 422 2,076.3 (1,880.2–2,272.3) 
>85 47 439.8 (382.7–496.7) 57 533.3 (464.2–602.4) 37 346.2 (301.3–391) 42 393 (342–443.9) 28.1 (24.4–31.7) 28.1 (24.4–31.7) 28.1 (24.4–31.7) 28.1 (24.4–31.7) 90 2,488.9 (1,981.2–2,996.7) 105 2,903.8 (2,356.5–3,451.1) 
Total 1,145 240.5 (228.9–252) 1,573 330.4 (314.4–346.3) 392 82.3 (78.4–86.3) 460 96.6 (91.9–101.3) 73 15.3 (14.6–16.1) 89 18.7 (17.8–19.6) 35 7.4 (7.0–7.7) 42 8.8 (8.4–9.2) 1,645 276.1 (262.8–289.5) 2,164 363.3 (348–378.5) 
ASR1  172.0 (147.2–196.9)  236.3 (202.2–270.5)  58.9 (50.4–67.4)  69.1 (59.1–79.1)  11.0 (9.4–12.6)  13.4 (11.4–15.3)  5.3 (4.5–6)  6.3 (5.4–7.2)  229.5 (217.3–241.6)  300.6 (286.7–314.5) 
ASR2  129.7 (127–132.3)  177 (173.8–180.1)  46.5 (44.9–48.1)  54.5 (52.8–56.2)  8.2 (7.6–8.9)  10 (9.2–10.7)  4.1 (3.6–4.5)  4.8 (4.3–5.3)  188.5 (177.5–199.5)  246.3 (233.7–258.8) 
ISICHSAHUNDTotal
first-ever strokestroke eventsfirst-ever strokestroke eventsfirst-ever strokestroke eventsfirst-ever strokestroke eventsfirst-ever strokestroke events
Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)Nrate (95% CI)
0–34 8.5 (1.9–18.1) 9.6 (2.1–20.4) 6.4 (1.4–13.6) 7.5 (1.6–15.9) 0 (0–0) 0 (0–0) 0 (0–0) 0 (0–0) 14 5.4 (2.6–8.3) 16 6.2 (3.2–9.3) 
35–44 33 36.6 (20.7–52.8) 39 43.3 (24.4–62.4) 19 21.1 (11.9–30.4) 23 25.5 (14.4–36.8) 2.2 (1.3–3.2) 2.2 (1.3–3.2) 0 (0–0) 0 (0–0) 54 52.3 (38.3–66.2) 64 62 (46.8–77.2) 
45–54 146 131.4 (108.7–153.9) 186 167.4 (138.6–196.2) 59 53.1 (43.9–62.2) 71 63.9 (52.9–74.9) 12 10.8 (8.9–12.6) 13 11.7 (9.7–13.7) 5.4 (4.5–6.3) 7.2 (6.0–8.4) 223 245.6 (213.4–277.8) 278 306.2 (270.3–342.1) 
55–64 340 429.3 (384–474.7) 474 598.5 (535.4–661.8) 96 121.2 (108.4–134) 113 142.7 (127.6–157.8) 21 26.5 (23.7–29.3) 26 32.8 (29.4–36.3) 11.4 (10.2–12.6) 12 15.2 (13.6–16.8) 466 601.1 (546.7–655.6) 625 806.3 (743.3–869.2) 
65–74 346 582.4 (531–633.9) 511 860.1 (784.2–936.1) 90 151.5 (138.1–164.9) 109 183.5 (167.3–199.7) 20 33.7 (30.7–36.6) 27 45.4 (41.4–49.5) 10.1 (9.2–11) 11.8 (10.7–12.8) 462 1,076.2 (978.6–1,173.8) 654 1,523.4 (1,407.6–1,639.3) 
75–84 225 696.6 (631.7–761.6) 297 919.6 (833.9–1,005.3) 85 263.2 (238.6–287.7) 95 294.1 (266.7–321.6) 15 46.4 (42.1–50.8) 18 55.7 (50.5–60.9) 11 34.1 (30.9–37.2) 12 37.2 (33.7–40.6) 336 1,653.1 (1,477.8–1,828.4) 422 2,076.3 (1,880.2–2,272.3) 
>85 47 439.8 (382.7–496.7) 57 533.3 (464.2–602.4) 37 346.2 (301.3–391) 42 393 (342–443.9) 28.1 (24.4–31.7) 28.1 (24.4–31.7) 28.1 (24.4–31.7) 28.1 (24.4–31.7) 90 2,488.9 (1,981.2–2,996.7) 105 2,903.8 (2,356.5–3,451.1) 
Total 1,145 240.5 (228.9–252) 1,573 330.4 (314.4–346.3) 392 82.3 (78.4–86.3) 460 96.6 (91.9–101.3) 73 15.3 (14.6–16.1) 89 18.7 (17.8–19.6) 35 7.4 (7.0–7.7) 42 8.8 (8.4–9.2) 1,645 276.1 (262.8–289.5) 2,164 363.3 (348–378.5) 
ASR1  172.0 (147.2–196.9)  236.3 (202.2–270.5)  58.9 (50.4–67.4)  69.1 (59.1–79.1)  11.0 (9.4–12.6)  13.4 (11.4–15.3)  5.3 (4.5–6)  6.3 (5.4–7.2)  229.5 (217.3–241.6)  300.6 (286.7–314.5) 
ASR2  129.7 (127–132.3)  177 (173.8–180.1)  46.5 (44.9–48.1)  54.5 (52.8–56.2)  8.2 (7.6–8.9)  10 (9.2–10.7)  4.1 (3.6–4.5)  4.8 (4.3–5.3)  188.5 (177.5–199.5)  246.3 (233.7–258.8) 

Stroke events include first-ever stroke and recurrent stroke; ASR1 indicates the aged-standardized rates to China census population 2010; ASR2 indicates the aged-standardized rates to WHO world standard population.

IS, ischemic stroke; ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage; UND, stroke of undetermined pathological type.

In all age groups, the overall incidence rates of stroke and all pathological types of strokes were higher in men than in women (online suppl. Table 1; for all online suppl. material, see https://doi.org/10.1159/000543474), these differences did not reach significance, and no significant differences in age-standardized incidence were noted. Among the pathological types of strokes, IS had the highest incidence (172.0 [95% CI, 147.2.4–196.9] and 236.3 [95% CI, 202.2–270.5] per 100,000 person-years, respectively), followed by ICH (58.9 [95% CI, 50.4–67.4] and 69.1 [95% CI, 59.1–79.1] per 100,000 person-years, respectively) and SAH (11.0 [95% CI, 9.4–12.6] and 13.4 [95% CI, 11.4–15.3] per 100,000 person-years, respectively) (Table 2). In men and women, the age-specific incidence of first-ever stroke and stroke events, as well as the three major pathological types of stroke (IS, ICH, and SAH), increases with age (online suppl. Table 1).

Online supplementary Table 2, Figures 1 and 2 show the incidences of first-ever stroke and stroke events in 31 provinces. The five provinces with the highest incidence of first-ever stroke per 100,000 population were Shaanxi (518.0 [95% CI, 418.9–617.14] per 100,000 person-years), Heilongjiang (400.8 [95% CI, 324.8–476.9] per 100,000 person-years), Ningxia (389.5 [95% CI, 251.0–528.1] per 100,000 person-years), Henan (366.6 [95% CI, 299.4–433.8] per 100,000 person-years), and Tianjin (344.0 [95% CI, 216.0–472.0] per 100,000 person-years). Conversely, the five provinces with the highest incidence of stroke events were Heilongjiang (672.7 [95% CI, 574.3–771.1] per 100,000 person-years), Shaanxi (603.1 [95% CI, 496.2–710.0] per 100,000 person-years), Henan (580.2 [95% CI, 495.7–664.7] per 100,000 person-years), Tianjin (469.0 [95% CI, 319.6–618.3] per 100,000 person-years), and Ningxia (456.2 [95% CI, 306.3–606.1] per 100,000 person-years). Hainan had the lowest incidence of first-ever stroke per 100,000 population (74.7 [95% CI, 13.9–135.5]), followed by Sichuan (85.1 [95% CI, 50.0–120.1]) and Beijing (93.0 [95% CI, 23.9–162.2]). Sichuan had the lowest incidence of stroke events per 100,000 population (96.1 [95% CI, 58.9–133.3]), followed by Beijing (102.9 [95% CI, 30.2–175.7]) and Shanghai (135.8 [95% CI, 55.8–215.9]). In addition, >6 times difference in first-ever stroke occurred between provincial regions with the highest (Shaanxi) and the lowest (Hainan) rates.

Fig. 1.

Incidence rates of first-ever stroke in 31 provinces in China.

Fig. 1.

Incidence rates of first-ever stroke in 31 provinces in China.

Close modal

The 7- and 30-day case fatality rates were 14.3% (95% CI, 12.6–16.0) and 17.8% (95% CI, 15.9–19.6) for patients with first-ever stroke, respectively. The 7- and 30-day case fatality rates were 13.1% (95% CI, 11.7–14.5) and 16.3% (95% CI, 14.8–17.9) for all patients with stroke including first-ever and recurrent strokes, respectively (Table 3). Significant differences in the 7- and 30-day case fatality rates of first-ever stroke and stroke events were found among different age groups. The case fatality rates were the lowest in the groups aged 55–64 and 45–54 years, and the highest case fatality rates were recorded in those aged 75–84 and >85 years. The 30-day case fatality rates of first-ever stroke were 14.3% (95% CI, 0–32.6) at 0–34 years, 13.0% (95% CI, 4.0–21.9) at 35–44 years, 10.8% (95% CI, 6.7–14.8) at 45–54 years, 8.6% (95% CI, 6.0–11.1) at 55–64 years, 14.7% (95% CI, 11.5–17.9) at 65–74 years, 31.3% (95% CI, 26.3–36.2) at 75–84 years, and 51.1% (95% CI, 40.8–61.4) at >85 years. The case fatality rate showed a U-shaped relationship with age (p < 0.0001). No significant difference in the 30-day case fatality rate was found between men and women (17.1% [95% CI, 14.6–19.5] vs. 18.6% [95% CI, 15.8–21.4]) (p = 0.437). Compared by area of residence, the 30-day mortality rate of first-ever stroke in rural areas was 19.8% (95% CI, 19.3–20.3), which was higher than that in urban areas with 14.9% (95% CI, 14.5–15.3) (p = 0.011). Significant differences in the 30-day mortality rate of different stroke subtypes were found, which were 8.3% (95% CI, 8.2–8.5) for IS, 44.4% (95% CI, 42.2–46.5) for ICH, and 3.1% (95% CI, 3.0–3.3) for SAH (p < 0.0001).

Table 3.

The case fatality rates (with 95% CI) at 7-day and 30-day after onset of stroke

7-day30-day
first-ever strokestroke eventsfirst-ever strokestroke events
rate (95% CI)p valuerate (95% CI)p valuerate (95% CI)p valuerate (95% CI)p value
Total 14.3 (12.59–16)  13.1 (11.7–14.5)  17.8 (15.9–19.6)  16.3 (14.76–17.9)  
Sex  0.479  0.677  0.437  0.682 
 Men 13.7 (11.49–16)  13.4 (11.47–15.3)  17.1 (14.6–19.5)  16.6 (14.53–18.7)  
 Women 15 (12.39–17.5)  12.8 (10.68–14.9)  18.6 (15.8–21.4)  15.9 (13.59–18.2)  
Age group  <0.001  <0.001  <0.001  <0.001 
 0–34 14.3 (0–32.6)  12.5 (0–28.7)  14.3 (0–32.6)  12.5 (0–28.7)  
 35–44 7.4 (0.42–14.4)  9.4 (2.23–16.5)  13 (4–21.9)  15.6 (6.73–24.5)  
 45–54 9.4 (5.58–13.3)  8.3 (5.04–11.5)  10.8 (6.69–14.8)  9.7 (6.23–13.2)  
 55–64 7.1 (4.75–9.4)  6.6 (4.62–8.5)  8.6 (6.04–11.1)  8.2 (6.01–10.3)  
 65–74 12.1 (9.15–15.1)  11 (8.61–13.4)  14.7 (11.49–17.9)  13.5 (10.84–16.1)  
 75–84 24.1 (19.53–28.7)  23 (18.97–27)  31.3 (26.29–36.2)  29.1 (24.81–33.5)  
 >85 42.2 (32.02–52.4)  41 (31.55–50.4)  51.1 (40.78–61.4)  49.5 (39.96–59.1)  
Residence  0.027  0.014  0.011  0.011 
 Urban 12 (11.72–12.3)  11.1 (10.83–11.3)  14.9 (14.51–15.3)  14 (13.66–14.3)  
 Rural 15.9 (15.56–16.3)  14.7 (14.38–15)  19.8 (19.31–20.3)  18 (17.66–18.4)  
Subtypes of stroke  <0.001  <0.001  <0.001  <0.001 
 IS 5.9 (5.81–6)  5.9 (5.81–5.9)  8.3 (8.21–8.5)  8.3 (8.19–8.4)  
 ICH 37.5 (35.74–39.3)  37.2 (35.57–38.8)  44.4 (42.22–46.5)  43.5 (41.55–45.4)  
 SAH 3.1 (2.99–3.3)  2.5 (2.41–2.6)  3.1 (2.99–3.3)  2.5 (2.41–2.6)  
 UND 37.1 (31.2–43.1)  31 (26.62–35.3)  40 (33.51–46.5)  33.3 (28.58–38.1)  
7-day30-day
first-ever strokestroke eventsfirst-ever strokestroke events
rate (95% CI)p valuerate (95% CI)p valuerate (95% CI)p valuerate (95% CI)p value
Total 14.3 (12.59–16)  13.1 (11.7–14.5)  17.8 (15.9–19.6)  16.3 (14.76–17.9)  
Sex  0.479  0.677  0.437  0.682 
 Men 13.7 (11.49–16)  13.4 (11.47–15.3)  17.1 (14.6–19.5)  16.6 (14.53–18.7)  
 Women 15 (12.39–17.5)  12.8 (10.68–14.9)  18.6 (15.8–21.4)  15.9 (13.59–18.2)  
Age group  <0.001  <0.001  <0.001  <0.001 
 0–34 14.3 (0–32.6)  12.5 (0–28.7)  14.3 (0–32.6)  12.5 (0–28.7)  
 35–44 7.4 (0.42–14.4)  9.4 (2.23–16.5)  13 (4–21.9)  15.6 (6.73–24.5)  
 45–54 9.4 (5.58–13.3)  8.3 (5.04–11.5)  10.8 (6.69–14.8)  9.7 (6.23–13.2)  
 55–64 7.1 (4.75–9.4)  6.6 (4.62–8.5)  8.6 (6.04–11.1)  8.2 (6.01–10.3)  
 65–74 12.1 (9.15–15.1)  11 (8.61–13.4)  14.7 (11.49–17.9)  13.5 (10.84–16.1)  
 75–84 24.1 (19.53–28.7)  23 (18.97–27)  31.3 (26.29–36.2)  29.1 (24.81–33.5)  
 >85 42.2 (32.02–52.4)  41 (31.55–50.4)  51.1 (40.78–61.4)  49.5 (39.96–59.1)  
Residence  0.027  0.014  0.011  0.011 
 Urban 12 (11.72–12.3)  11.1 (10.83–11.3)  14.9 (14.51–15.3)  14 (13.66–14.3)  
 Rural 15.9 (15.56–16.3)  14.7 (14.38–15)  19.8 (19.31–20.3)  18 (17.66–18.4)  
Subtypes of stroke  <0.001  <0.001  <0.001  <0.001 
 IS 5.9 (5.81–6)  5.9 (5.81–5.9)  8.3 (8.21–8.5)  8.3 (8.19–8.4)  
 ICH 37.5 (35.74–39.3)  37.2 (35.57–38.8)  44.4 (42.22–46.5)  43.5 (41.55–45.4)  
 SAH 3.1 (2.99–3.3)  2.5 (2.41–2.6)  3.1 (2.99–3.3)  2.5 (2.41–2.6)  
 UND 37.1 (31.2–43.1)  31 (26.62–35.3)  40 (33.51–46.5)  33.3 (28.58–38.1)  

Figure 3 shows the case fatality rates of first-ever stroke by province. Large differences were found between different provinces. Tibet and Shanghai had the highest and lowest 30-day case fatality rates, respectively, with a nearly 20-fold gap between them.

Fig. 2.

Incidence rates of stroke events in 31 provinces in China.

Fig. 2.

Incidence rates of stroke events in 31 provinces in China.

Close modal

The NESS-China study has provided the age-standardized prevalence, incidence, and mortality rates for stroke among China adults aged ≥20 years in 2012–2013 [4]. However, the incidence of stroke events in all age groups is not defined, and the high recurrence rate of stroke is one of its significant characteristics. On the basis of the original database, we further extracted, sorted out, and analyzed the incidence of first-ever stroke and stroke events and the case fatality rates in all age groups. The present study revealed new population-based epidemiologist data on stroke in China. In our study, the ratio of recurrent strokes (24%) was close to the one-quarter ratio in Oxford Vascular Study and higher than one population-based study in Ireland (14.6%) [6, 15, 16]. The ratios of ICH (23.8% of first-ever strokes and 21.3% of stroke events) were comparable to the rate (14–27%) reported in low- and middle-income countries (LMICs) and higher than that (9–13%) in high-income countries (HICs) [17, 18]. Compared with the results of previous studies in China (28–55%), the proportion of ICH has significantly reduced [12, 19]. This may be related to the effectiveness of hypertension prevention and control in recent years, and 73% of the stroke burden can be attributed to hypertension in China [20]. From the rates of first-ever IS (72.8%, 1,145/1,573) and first-ever ICH (85.2%, 392/460), we can find that the recurrence rate of IS was higher than that of hemorrhagic stroke, which may be related to the mortality rate of stroke of different pathological types and prevention-related risk factors [21‒23].

The age-standardized incidence rate of total stroke to China census population in 2010 greatly increases with age. Meanwhile, we noted that incidence of ischemic stroke was lower in age group >85 years old, both in men and women, compared with that observed in younger age bands. Another study about risk factors for incident stroke and its subtypes in China was also shown that the incidences of ischemic stroke was lower in age ≥80 years old compared with that observed in the younger age group [24]. Analysis of the incidence of TIAs in our survey showed that the highest incidence was in the age group 65–74 years, while the 75–84 age group and ≥85 years of age decreased sequentially [25]. We speculate that this phenomenon may be related to pathogenesis, which requires further research to confirm. Furthermore, the incidence of stroke is related to the level of economic development of the country. There was a strong linear relationship between crude incidence rates and the percentage of the population aged ≧65 years in both LMICs and HICs. In regression analyses undertaken between crude incidence rate and the study year, there was a negative relationship in HICs, but a strong positive relationship for LMICs [26]. The burden of stroke in China is severe, and we estimated ≈3.1 million stroke events, including approximately 2.3 million IS events and 0.8 million hemorrhagic stroke events, when we applied to the whole Chinese population. Thus, the burden of stroke in China required arduous tasks of stroke primary and secondary prevention and risk factors control.

In China, studies have shown geographic differences and north-south gradient trends in stroke burden [4, 27], which may be the result of a combination of regional differences in geographical location, climatic factors, socioeconomic and stroke-related risk factors [28, 29]. We further presented the incidence of first-ever stroke and stroke events in 31 provincial regions (Fig. 1 and 2; online suppl. Table 2), showing differences in stroke burden in different provinces in the same region. Most provinces with a high incidence of first-ever stroke were also associated with a high incidence of stroke events, which can be explained by the high recurrence rate of stroke (Fig. 3). Although the rates of first-ever stroke were comparable in some provinces, a difference in the recurrence rates was noted, which may be related to the control of stroke-related risk factors, such as the treatments of hypertension, diabetes mellitus, and dyslipidemia and smoking-cessation programs, which improved the health of the overall population [21, 22, 30].

Fig. 3.

Case fatality rates of first-ever stroke at 7 and 30 days in 31 provinces in China.

Fig. 3.

Case fatality rates of first-ever stroke at 7 and 30 days in 31 provinces in China.

Close modal

The lower case fatality can lead to declining mortality and increasing prevalence, and a high prevalence leads to high recurrence rates. This prompted us to further analyze the case fatality rates. Some studies have shown that the global 30-day case fatality rate is 17–30% in HICs and 18–35% in LMICs [12], and the 30-day stroke case fatality rate in China is relatively low. The 30-day case fatality rate of IS in China (8.3%, 95% CI, 8.2–8.5%) was significantly lower than that of ICH. The case fatality rate of stroke is an important epidemiological indicator. In the case fatality rate analysis, the case fatality rates of first-ever stroke at 7 and 30 days were 14.3% and 17.8%, respectively, and the case fatality rates of stroke events were 13.1% and 16.3%, respectively. In this study, 80% of the cumulative case fatality rates at 30 days occurred within 1 week of onset, consistent with the results of a previous study [31]. There continues to be a significant variation in stroke case fatality both between and among LMICs and HICs [26]. This is comparable to the global 30-day case fatality rate of reported in HICs (17–30%) and in LMICs (18–35%) [17]. In China, the 30-day case fatality rate of stroke is relatively low. We found that the 30-day case fatality rate of IS in China (8.3%, 95% CI, 8.2–8.5%) was significantly lower than that of ICH (44.4%, 95% CI, 42.2%–46.5%) (p < 0.001). The worldwide 30-day case fatality of IS was 13.5% (95% CI, 12.3–14.7%). In Asia, the case fatality rate was 10.8% (95% CI, 8.3–13.5%), which was lower those in Europe (14.2%, 95% CI, 12.6–15.9%), South America and Caribbean (14.0%, 95% CI, 11.2–17.1%), North America (14.0%, 95% CI, 9.5–19.1%), and Australia and New Zealand (12.5%, 95% CI, 11.1–13.9%) [32].

The case fatality rates of SAH are decreasing with substantial between-country variation [33]. In our study, the case fatality rate of SAH (3.1%) was lower than that reported in the literature (41–31%) [33]. China stroke statistics report showed that the inhospital outcomes of SAH cases admitted to hospitals in the Hospital Quality Monitoring System in 2019 were discharge (72.7% and 65.3%), transfer (3.7% and 11.2%), discharge against medical advice (16.3% and 19.3%), death (4.3% and 3.3%), and unclear (3.0% and 4.2%) in the tertiary public hospitals and secondary public hospitals/private hospitals [34]. The length of stay in hospitals was 14.6 ± 14.4 days and 10.4 ± 13.3 days, respectively [34]. The hospital-based rate of death was similar to our findings. Although the part of discharge against medical advice may be include partial death, the case fatality rate of SAH was lower. The lower case fatality rate might be largely due to the result of improved medical treatment. Furthermore, our survey was a population-based epidemiological survey, and there was a category of UND in addition to IS, ICH, SAH, in which stroke cases with no brain imaging done within the first week of stroke onset, or when the results of the imaging were not available for review by the study neurologist, were classified as UND. Therefore, we analyzed that a certain proportion of SAH patients who were critically ill and could not obtain radiographic evidence were classified into the UND group, and the case fatality rate of UND was 37.1%. The presence of UND does have an impact on stroke rates by etiological classification, but it is an unavoidable special category of population-based surveys. Stroke etiology, patient age, and stroke severity were the main predictors of 28-day case fatality [31, 32]. The proportion of stroke etiology varies between ethnicities, which may be one explanation. Asia has a lower proportion of cardioembolism and a high proportion of small-vessel occlusion, characterized by a lower 30-day case fatality rate [35, 36].

Age is a nonmodifiable risk factor for stroke and is strongly associated with increased mortality and worsening functional outcomes after a stroke [37, 38]. The overall 30-day case fatality rate of patients with first-ever stroke was 17.8% (292/1,645), and the 30-day case fatality rate stratified by age showed a U-shaped relationship (p < 0.0001). The case fatality rate was the lowest in the group aged 55–64 years and was higher in patients aged <55 years than in those aged 55–64 years. This phenomenon may be related to the different causes of stroke at different ages. The specific reasons need to be further studied. No significant difference was found in the 30-day case fatality rate between men and women (p = 0.4003). This result was consistent with the finding of a meta-analysis, which showed that the mortality rate was higher in women mostly because of age, as well as stroke severity, atrial fibrillation, and pre-stroke functional limitations [39].

Compared with urban and rural areas, the 30-day case fatality rate of stroke in rural areas was 19.8% higher than that in urban areas (14.9%) (p = 0.0103). Figure 3 shows the case fatality rates of first-ever stroke in 31 provinces, and some provinces (Tibet, Fujian, Beijing, Gansu, Guangxi, Xinjiang, Qinghai, and Hunan) have high case fatality rates. The above two phenomena have two explanations. First, the levels of economic development and medical treatment in urban areas are higher than that in rural regions in China, whereas provinces, such as Tibet, Xinjiang, and Qinghai, are geographically remote and have weak medical treatment levels. Second, given the characteristics of transportation conditions and scattered residences, higher prehospital delays, or even lack of hospital treatments at all, result in a high case fatality rate in rural areas and remote provinces [2]. Third, a large gap remains in stroke prevention in China, particularly in rural regions and remote provinces. There are gaps among both residents and community physicians, and they are lack of clinical practice guidelines knowledge [12, 40]. Beijing also has relatively high case fatality rates and has two survey sites, with a small sample and 11 confirmed first-ever stroke cases, which limited representativeness. The 30-day case fatality rates of 31 provinces were divergent across regions. Further studies are needed to explain the regional disparities, which will certainly help in the formulation and implementation of stroke prevention and control policies, and thus guide efforts to reduce the burden of stroke.

Our study is the first large-scale cross-sectional survey of cerebrovascular diseases in China, with a rigorous design and standardized investigation. There are still two potential limitations to our research. On the one hand, there was recall bias in cross-sectional surveys, especially in patients with mild strokes, which can lead to an underestimation of incidence. But door-to-door surveys and detailed interviews were used by CDC investigators to minimize the occurrence of the recall biases cases as much as possible. On the other hand, there were some stroke cases without CT/MRI imaging evidences, especially in less developed provinces or rural areas with poor transportation. So there was a small percentage of the stroke cases that is difficult-to-classify in the etiological classification of the survey results.

The authors thank all the CDC staff and the neurologists from the 31 provinces who worked hard to ensure the accuracy of the data.

This study protocol was reviewed and approved by the Ethics Committee of the Beijing Tiantan Hospital affiliated with the Capital Medical University, Approval No. [2011BAI08B00]. Written informed consent was obtained from all participants by interviewers before data collection.

The authors have no conflicts of interest.

This study was funded by the Ministry of Science and Technology of China (reference number 2011BAI08B01).

Haixin Sun drafted the manuscript, with input from Bin Jiang and Wenzhi Wang. All authors reviewed the draft and approved the final version. Wenzhi Wang, Limin Wang, and Bin Jiang designed the survey. Haixin Sun, Xiaojuan Ru, Dongling Sun, and Mei Zhang supervised survey conduct and were responsible for the data collection. Siqi Ge, Xiaojuan Ru, and Haixin Sun managed the database and did the statistical analyses.

Data collected for the study, including de-identified individual participant data and a data dictionary, will be made available upon reasonable request and after applicants have signed appropriate data sharing agreements. Please send data access requests to the corresponding authors. Such requests must be approved by the respective Ethics Boards and appropriate data custodians. All data will be available from the time of publication, with no end date.

1.
GBD 2015 DALYs and HALE Collaborators
.
Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015
.
Lancet
.
2016
;
388
(
10053
):
1603
58
.
2.
Liu
L
,
Wang
D
,
Wong
KS
,
Wang
Y
.
Stroke and stroke care in China: huge burden, significant workload, and a national priority
.
Stroke
.
2011
;
42
(
12
):
3651
4
.
3.
Feigin
VL
,
Forouzanfar
MH
,
Krishnamurthi
R
,
Mensah
GA
,
Connor
M
,
Bennett
DA
, et al
.
Global and regional burden of stroke during 1990-2010: findings from the global burden of disease study 2010
.
Lancet
.
2014
;
383
(
9913
):
245
54
.
4.
Wang
W
,
Jiang
B
,
Sun
H
,
Ru
X
,
Sun
D
,
Wang
L
, et al
.
Prevalence, incidence, and mortality of stroke in China: results from a nationwide population-based survey of 480 687 adults
.
Circulation
.
2017
;
135
(
8
):
759
71
.
5.
Chen
Z
,
Jiang
B
,
Ru
X
,
Sun
H
,
Sun
D
,
Liu
X
, et al
.
Mortality of stroke and its subtypes in China: results from a nationwide population-based survey
.
Neuroepidemiology
.
2017
;
48
(
3–4
):
95
102
.
6.
Hankey
GJ
.
Secondary stroke prevention
.
Lancet Neurol
.
2014
;
13
(
2
):
178
94
.
7.
Koton
S
,
Pike
JR
,
Johansen
M
,
Knopman
DS
,
Lakshminarayan
K
,
Mosley
T
, et al
.
Association of ischemic stroke incidence, severity, and recurrence with dementia in the atherosclerosis risk in communities cohort study
.
JAMA Neurol
.
2022
;
79
(
3
):
271
80
.
8.
Pendlebury
ST
.
Stroke-related dementia: rates, risk factors and implications for future research
.
Maturitas
.
2009
;
64
(
3
):
165
71
.
9.
Sibbritt
PD
,
Peng
DW
,
Hosseini
DM
,
Maguire
PJ
,
Bayes
J
,
Adams
PJ
.
An examination of modifiable risk factors in stroke survivors, with a view to recurrent stroke prevention
.
J Stroke Cerebrovasc Dis
.
2022
;
31
(
8
):
106547
.
10.
Jiang
G
,
Li
W
,
Wang
D
,
Shen
C
,
Ji
Y
,
Zheng
W
.
Epidemiological transition and distribution of stroke incidence in Tianjin, China, 1988-2010
.
Publ Health
.
2016
;
131
:
11
9
.
11.
Wang
WZ
,
Jiang
B
,
Wu
SP
,
Hong
Z
,
Yang
QD
,
Sander
JW
, et al
.
Change in stroke incidence from a population-based intervention trial in three urban communities in China
.
Neuroepidemiology
.
2007
;
28
(
3
):
155
61
.
12.
Liu
M
,
Wu
B
,
Wang
WZ
,
Lee
LM
,
Zhang
SH
,
Kong
LZ
.
Stroke in China: epidemiology, prevention, and management strategies
.
Lancet Neurol
.
2007
;
6
(
5
):
456
64
.
13.
Aho
K
,
Harmsen
P
,
Hatano
S
,
Marquardsen
J
,
Smirnov
VE
,
Strasser
T
.
Cerebrovascular disease in the community: results of a WHO collaborative study
.
Bull World Health Organ
.
1980
;
58
(
1
):
113
30
.
14.
The World Health Organization
.
The world health organization monica project (monitoring trends and determinants in cardiovascular disease): a major international collaboration
.
J Clin Epidemiol
.
1988
;
41
(
2
):
105
14
.
15.
Rothwell
PM
,
Coull
AJ
,
Giles
MF
,
Howard
SC
,
Silver
LE
,
Bull
LM
, et al
.
Change in stroke incidence, mortality, case-fatality, severity, and risk factors in Oxfordshire, UK from 1981 to 2004 (Oxford Vascular Study)
.
Lancet
.
2004
;
363
(
9425
):
1925
33
.
16.
kelly-et-al-2012-incidence-event-rates-and-early-outcome-of-stroke-in-dublin-Ireland.
17.
Feigin
VL
,
Lawes
CM
,
Bennett
DA
,
Barker-Collo
SL
,
Parag
V
.
Worldwide stroke incidence and early case fatality reported in 56 population-based studies: a systematic review
.
Lancet Neurol
.
2009
;
8
(
4
):
355
69
.
18.
Krishnamurthi
RV
,
Barker-Collo
S
,
Parag
V
,
Parmar
P
,
Witt
E
,
Jones
A
, et al
.
Stroke incidence by major pathological type and ischemic subtypes in the auckland regional community stroke studies: changes between 2002 and 2011
.
Stroke
.
2018
;
49
(
1
):
3
10
.
19.
Zhang
LF
,
Yang
J
,
Hong
Z
,
Yuan
GG
,
Zhou
BF
,
Zhao
LC
, et al
.
Proportion of different subtypes of stroke in China
.
Stroke
.
2003
;
34
(
9
):
2091
6
.
20.
Feigin
VL
,
Roth
GA
,
Naghavi
M
,
Parmar
P
,
Krishnamurthi
R
,
Chugh
S
, et al
.
Global burden of stroke and risk factors in 188 countries, during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013
.
Lancet Neurol
.
2016
;
15
(
9
):
913
24
.
21.
Oza
R
,
Rundell
K
,
Garcellano
M
.
Recurrent ischemic stroke: strategies for prevention
.
Am Fam Physician
.
2017
;
96
(
7
):
436
40
.
22.
Arima
H
,
Chalmers
J
.
PROGRESS: prevention of recurrent stroke
.
J Clin Hypertens
.
2011
;
13
(
9
):
693
702
.
23.
Liu
J
,
Zhao
D
,
Wang
W
,
Sun
JY
,
Li
Y
,
Jia
YN
.
[Trends regarding the incidence of recurrent stroke events in Beijing]
.
Zhonghua Liu Xing Bing Xue Za Zhi
.
2007
;
28
(
5
):
437
40
.
24.
Qi
W
,
Ma
J
,
Guan
T
,
Zhao
D
,
Abu-Hanna
A
,
Schut
M
, et al
.
Risk factors for incident stroke and its subtypes in China: a prospective study
.
J Am Heart Assoc
.
2020
;
9
(
21
):
e016352
.
25.
Jiang
B
,
Sun
H
,
Ru
X
,
Sun
D
,
Chen
Z
,
Liu
H
, et al
.
Prevalence, incidence, prognosis, early stroke risk, and stroke-related prognostic factors of definite or probable transient ischemic attacks in China, 2013
.
Front Neurol
.
2017
;
8
:
309
.
26.
Thayabaranathan
T
,
Kim
J
,
Cadilhac
DA
,
Thrift
AG
,
Donnan
GA
,
Howard
G
, et al
.
Global stroke statistics 2022
.
Int J Stroke
.
2022
;
17
(
9
):
946
56
.
27.
Ru
X
,
Wang
W
,
Sun
H
,
Sun
D
,
Fu
J
,
Ge
S
, et al
.
GeographicalDifference, rural-urban transition and trend in stroke prevalence in China: findings from a national epidemiological survey of stroke in China
.
Sci Rep
.
2019
;
9
(
1
):
17330
.
28.
Li
Y
,
Wang
L
,
Feng
X
,
Zhang
M
,
Huang
Z
,
Deng
Q
, et al
.
Geographical variations in hypertension prevalence, awareness, treatment and control in China: findings from a nationwide and provincially representative survey
.
J Hypertens
.
2018
;
36
(
1
):
178
87
.
29.
Wu
S
,
Wu
B
,
Liu
M
,
Chen
Z
,
Wang
W
,
Anderson
CS
, et al
.
Stroke in China: advances and challenges in epidemiology, prevention, and management
.
Lancet Neurol
.
2019
;
18
(
4
):
394
405
.
30.
Lackland
DT
,
Roccella
EJ
,
Deutsch
AF
,
Fornage
M
,
George
MG
,
Howard
G
, et al
.
Factors influencing the decline in stroke mortality: a statement from the American Heart Association/American Stroke Association
.
Stroke
.
2014
;
45
(
1
):
315
53
.
31.
Gauthier
V
,
Cottel
D
,
Amouyel
P
,
Dallongeville
J
,
Meirhaeghe
A
.
Large disparities in 28-day case fatality by stroke subtype: data from a French stroke registry between 2008 and 2017
.
Eur J Neurol
.
2021
;
28
(
7
):
2208
17
.
32.
Zhang
R
,
Wang
Y
,
Fang
J
,
Yu
M
,
Wang
Y
,
Liu
G
.
Worldwide 1-month case fatality of ischaemic stroke and the temporal trend
.
Stroke Vasc Neurol
.
2020
;
5
(
4
):
353
60
.
33.
Mahlamäki
K
,
Rautalin
I
,
Korja
M
.
Case fatality rates of subarachnoid hemorrhage are decreasing with substantial between-country variation: a systematic review of population-based studies between 1980 and 2020
.
Neuroepidemiology
.
2022
;
56
(
6
):
402
12
.
34.
Wang
YJ
,
Li
ZX
,
Gu
HQ
,
Zhai
Y
,
Zhou
Q
,
Jiang
Y
, et al
.
China stroke statistics: an update on the 2019 report from the national center for healthcare quality management in neurological diseases, China national clinical research center for neurological diseases, the Chinese stroke association, national center for chronic and non-communicable disease control and prevention, Chinese center for disease control and prevention and Institute for global neuroscience and stroke collaborations
.
Stroke Vasc Neurol
.
2022
;
7
(
5
):
415
50
.
35.
Gezmu
T
,
Schneider
D
,
Demissie
K
,
Lin
Y
,
Gizzi
MS
.
Risk factors for acute stroke among South Asians compared to other racial/ethnic groups
.
PLoS One
.
2014
;
9
(
9
):
e108901
.
36.
Sen
S
,
Dahlberg
K
,
Case
A
,
Paolini
S
,
Burdine
J
,
Peddareddygari
LR
, et al
.
Racial-ethnic differences in stroke risk factors and subtypes: results of a prospective hospital-based registry
.
Int J Neurosci
.
2013
;
123
(
8
):
568
74
.
37.
Abdo
R
,
Abboud
H
,
Salameh
P
,
El Hajj
T
,
Hosseini
H
.
Mortality and predictors of death poststroke: data from a multicenter prospective cohort of Lebanese stroke patients
.
J Stroke Cerebrovasc Dis
.
2019
;
28
(
4
):
859
68
.
38.
Wei
W
,
Li
S
,
San
F
,
Zhang
S
,
Shen
Q
,
Guo
J
, et al
.
Retrospective analysis of prognosis and risk factors of patients with stroke by TOAST
.
Medicine
.
2018
;
97
(
15
):
e0412
.
39.
Phan
HT
,
Blizzard
CL
,
Reeves
MJ
,
Thrift
AG
,
Cadilhac
D
,
Sturm
J
, et al
.
Sex differences in long-term mortality after stroke in the instruct (INternational STRoke oUtComes sTudy): a meta-analysis of individual participant data
.
Circ Cardiovasc Qual Outcomes
.
2017
;
10
(
2
):
e003436
.
40.
Chen
C
,
Qiao
X
,
Kang
H
,
Ding
L
,
Bai
L
,
Wang
J
.
Community physicians' knowledge of secondary prevention after ischemic stroke: a questionnaire survey in Shanxi Province, China
.
BMC Med Educ
.
2015
;
15
:
197
.