Li Wu
Zeming Ye2†
Ming Luo
Shaojun Li
Yongjun Jiang- 1Department of Neurology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- 2Guangzhou Panyu District Hexian Memorial Hospital, Guangzhou, China
Background: Epilepsy is one of the leading neurological diseases. Our study is aimed to determine whether there is a focal region of high epilepsy prevalence in China.
Methods: All studies published between 1981 and 2020 investigating the prevalence of epilepsy in China were systematically reviewed. The geographical location, sample size, number of cases, urbanization rate, gross domestic product (GDP) per capita, percentage of <15 years old, and medical insurance per capita were derived and analyzed. Criteria for a provincial region of high prevalence was defined as with higher epilepsy prevalence than the average prevalence of epilepsy in China.
Results: A total of 60 studies provided data on the prevalence of epilepsy in 29 of 33 provincial regions of China. The average prevalence in China was 1.68 per 1,000, and 12 provincial regions met our criteria for a region of high epilepsy prevalence and constitute an epilepsy belt ranging along the division between the second step and the third step of China. The prevalence in the epilepsy belt was 331.9 per 100,000 population compared with 125.3 per 100,000 in regions outside the belt (P < 0.05). Surprisingly, there was no significant difference in sample size, number of cases, urbanization rate, GDP per capita, percentage of <15 years old, or medical insurance per capita between the regions in and outside the epilepsy belt.
Conclusions: An epilepsy belt of high prevalence exists in 12 provincial regions locating along the division between the second step and the third step of China.
Background
Epilepsy is one of the commonest chronic neurological disorders, affects people of all races, ages and locations in the worldwide and causes severe burden to society. After a long period of repetitive seizures, patients probably would suffer from sense of shame on epilepsy, decline of intelligence and social viability, and increased suicide rate and unintentional mortality. The global death due to epilepsy increases from 130,200 to 177,600 from 1990 to 2010 (1). In addition to the high mortality, epilepsy also induces disability, which is reflected by the remarkable years lived with disability (YLDs) and disability-adjusted life-years (DALYs). The possible reason is that a large portion of patients with epilepsy are young patients. It is estimated that there are 70 million patients with epilepsy in the world while the incidence and prevalence of epilepsy are different among different regions (2). People in poor regions are prone to have epilepsy with the prevalence of 10–40 per 1,000 in developing countries like sub-Saharan Africa and 4.9 per 1,000 in developed countries like Europe.
China has achieved great success in the economy in the last four decades since 1978, the year the policy of Reform and Open up was established. Thanks to the economic miracle, China has made enormous strides in health improvement like the longer life expectancy (60.4 in 1970 to 72.9 in 2010 for male; 63.5 to 79.0 for female). Unlike the increased mortality in the worldwide, the death caused by epilepsy has decreased by 34.8% from 1990 to 2010 (from 187,000 to 122,000) (3). The DALYs has also decreased from 1,723,100 to 1,597,400. A recent systematic review summarized the variable epilepsy prevalence in different regions of China and analyzed the possible issues (4). As the authors pointed out, the geography may contribute to the prevalence of epilepsy since there are tremendous differences of economic development, ethic, and medical policy among different regions in China Mainland. Previous studies have suggested that stroke belt, another common neurological disorder, exists in United States (5) and China Mainland (6). Thus, we hypothesized that there may be an epilepsy belt in China as many individual studies have shown the geographic variation of epilepsy prevalence.
Methods
Search strategy
We performed the search on the international databases PubMed, ISI Web of Science, Scopus, and Embase, and the Chinese databases China National Knowledge Infrastructure (CNKI) and Chinese Wanfang Data from the established date to December 2020 using the terms “epilepsy AND (prevalence OR epidemiology) AND (China OR Chinese).” Relevant studies were also checked from the reference lists.
Selection criteria
Publications met the following criteria were used for further analysis: (1) Complete population-based case ascertainment in China. (2) Publications provided the prevalence of epilepsy. (3) Epilepsy diagnosis was made according to the criteria of the World Health Organization (WHO) or International League against Epilepsy (ILAE) or the local guideline. (4) Studies were published in Chinese or English. The studies were excluded if they were sampled in specific areas like a hospital. Moreover, if two or more publications reported the same study of the same population, only one publication would be included.
Classification of geographical regions
As the third largest country in the world, China has an area of 9.6 million square kilometers and a coastline of 18,000 km. It spans ~50 degrees of latitude and 62 degrees of longitude, and includes plains, basins, plateaus, foothills, and mountains. In which rugged plateaus, foothills and mountains occupy nearly 70% of the whole land, and form a topographic feature higher in the West and lower in the East like a three-step ladder (7). Base on locations, it has been divided into 34 provincial regions, which contains 23 provinces (Taiwan included), five autonomous regions, four municipalities and two special administrative regions (Macao and Hong Kong) (8). In this study, Chongqing was merged into Sichuan Province, since Chongqing had been a city in Sichuan Province until 1997, and some of the researches used were conducted before 1997. In total, 29 out of 33 provincial regions were included.
Sources of data for epilepsy prevalence
If only one study was available for the prevalence of epilepsy in a provincial region, the single-source was accepted. If more than one eligible study were available for the prevalence of epilepsy in a provincial region, the prevalence rates from all sources were combined to produce an average rate which was weighted according to the sample size. If no study was available for the prevalence of epilepsy in a provincial region, the prevalence rate of this provincial region was noted as N/A.
Illustration of the survey methods
In most of the studies we included, the investigators used a random cluster sample survey method to select the cluster where they would go to do the following survey, with a street, village or town in a specific region constituting one cluster. During the following epidemiological survey (mostly door-to-door survey), the residents answered a written questionnaire with the help of well-trained investigators, and then were evaluated by board-certified neurologists at home or in hospitals (9, 10).
Clue investigation was mainly used in vast rural areas where door-to-door survey was impractical. It was a community-based screening strategy among defined population which required employed well-trained local physicians or health workers to collect all clues available to discover patients within a study period (11–13).
One-stage detection method was a community-based screening method which gathered participating residents in the place of screening service activity (a community center or other high-traffic area), where the residents answered a written questionnaire with the help of well-trained social workers, and then were evaluated by board-certified neurologists at the same place (14).
Geographical classification of epilepsy prevalence and definition of the epilepsy belt
Provincial regions with epilepsy prevalence higher than the average epilepsy prevalence in China were classified as regions with high epilepsy prevalence. The epilepsy belt was defined as a region containing provincial regions with high epilepsy prevalence.
Exploring possible causes of the epilepsy belt
To explore the possible causes of the epilepsy belt, we reviewed Chinese nationwide epidemiological surveys to obtain the prevalence of risk factors for epilepsy, such as poverty, young age and countryside. Urbanization rate, GDP per capita, percentage of <15 years old and per capita medical insurance in 2018 were retrieved from China Yearbook of Statistics and China Yearbook of Health Statistics. To increase homogeneity, we did not combine the data from multisource, only those from the most representative survey were analyzed. If only 1 source was available for the data of a given factor, the single-source was accepted. If multiple sources were available for the data of a given risk factor, the survey with larger sample size was selected.
Data extraction
Publications were appraised by two independent investigators (LW and ZY) and any disagreement was settled by the third investigators (YL). The information of the studies, i.e., the first author's name, year of survey, geographic location, age limitation, sample size, gender of population, urban or suburban, and case size, has been extracted.
Statistical analysis
Epilepsy prevalence in the 33 provincial regions of China including Hong Kong, Macao, and Taiwan was analyzed. Crude epilepsy prevalence rates were reported as the number of cases of epilepsy at the research point per 1,000 individuals. After determining the epilepsy belt, the overall epilepsy prevalence in the epilepsy belt was calculated from the corresponding provincial prevalence rates by weighting the provincial population size. Distribution of risk factors for epilepsy, such as urbanization rate, GDP per capita, percentage of <15 years old and per capita medical insurance in provincial regions, was obtained from nationwide epidemiological surveys. Using these provincial data, distribution of risk factors in epilepsy belt and regions outside was calculated by weighting the provincial population size. Provincial epilepsy prevalence and possible influential factors in population were ranked, with their relationship analyzed by Spearman rank correlation. Differences in risk factor distribution between epilepsy belt and regions outside were compared using 1-way ANOVA, with provincial data treated as unit of analysis. A P < 0.05 was defined as statistical significance.
Results
Results of literature searching and quality of the included studies
The database search for studies on epilepsy prevalence in China yielded 456 articles. The abstracts of these articles were screened and in which 395 did not meet the eligibility criteria. The remaining 56 papers have been read thoroughly, and the relevant references have been tracked, an additional four publications have identified. Eventually, 60 studies (60 publications) met the selection criteria for eligibility and had been analyzed. Table 1 showed the characteristics of these included studies. The 60 eligible studies provided data for the prevalence of epilepsy in 29 (87.88%, including Hong Kong) of the 33 provincial regions in total. In the 60 included studies, 39 of them used door-to-door survey method. The diagnosis of epilepsy was confirmed by specialized doctors. For epilepsy diagnostic criteria, 38 of 60 studies used WHO criteria or ILAE criteria, and the other 22 studies used local guideline criteria. The sampling rates of the 29 provincial regions from the enrolled 60 studies were shown in Figure 1, and were distinct across the country, higher in central area and Southeast regions and lower in West regions.
Table 1. Characteristics of the included epidemiological surveys on epilepsy prevalence in China.
Figure 1. Sampling rates of the 29 provincial regions from the enrolled 60 studies were shown. The sampling rates [(sampling size/numbers of population in 2018) × 1,000‰] were distinct across the country, higher in central area and Southeast regions and lower in West regions.
Epilepsy prevalence in provincial regions
Table 2 showed the epilepsy prevalence in the 29 provincial regions of China in rank order. The average prevalence of epilepsy was 1.68 per 1,000 in the whole China. The prevalence of epilepsy was highest in Heilongjiang (807.8 per 100,000 population) followed by Tibet (Xizang Zizhiqu; 532.4 per 100,000 population), and lowest in Fujian (20.5 per 100,000 population) and Jiangxi (20.2 per 100,000 population). The difference in epilepsy prevalence between the highest and the lowest provincial regions was more than 39 times. Figure 2 was a color-coded map of China showing the prevalence of epilepsy in the 29 provincial regions with different color representing different prevalence.
Table 2. Epilepsy prevalence in 29 provincial regions of China.
Figure 2. A color-coded map of China showing the prevalence of epilepsy [(case/sampling size) × 1,000‰] in the 33 provincial regions with different color representing different prevalence. In this map, the epilepsy belt was highlighted with deeper colors.
The epilepsy belt
The 12 provincial regions that met our criteria for a region of high epilepsy prevalence included Heilongjiang, Shanxi, Tibet, Hubei, Henan, Jilin, Beijing, Taiwan, Hebei, Guangxi, Guizhou, and Hunan, and constituted a near continuous belt. The prevalence of epilepsy in the epilepsy belt was per 331.9 per 100,000 population compared with 125.3 in regions outside the belt (P < 0.05). Except for Tibet and Taiwan, this belt located along the Daxing'an, Taihang, Wu and Xuefeng Mountains, which is the division between the second step and the third step of China. This line-shaped belt was interrupted by the Inner Mongolia, in which there has been no epilepsy prevalence survey.
According to the 2018 China Census, the national population (excluding Taiwan, Hong Kong, and Macao) was 1.395 billion, of whom 592.47 million (44.00%) resided in the epilepsy belt, and 753.78 million (56.00%) outside the belt. The epilepsy belt covered 34.76% (3.337/9.6 million km2) of China's territory. The overall prevalence of epilepsy in China was 1.68 per 1,000, but the prevalence of epilepsy in the epilepsy belt was 3.32 per 1,000 compared with 1.25 per 1,000 in other regions (P < 0.001). The prevalence of epilepsy in the belt was more than 2 times of that in other regions.
Prevalence of epilepsy in different provincial regions over time
Figure 3 showed epilepsy prevalence of six provincial regions in different years. In Shandong Province, the prevalence of epilepsy was 3.54 per 1,000 in 1985, and declined to 0.84 per 1,000 in 1987, stayed at 0.86 per 1,000 in 1996 and 0.88 per 1,000 in 2011. In Jiangsu Province, the epilepsy prevalence was lowest in 1987 (0.55 per 1,000) and highest in 2000 (7.83 per 1,000), and declined to 3.78 per 1,000 in 2001 and 1.71 per 1,000 in 2012. In Ningxia Province, the prevalence of epilepsy was 4.13 per 1,000 in 1983, and declined to 0.99 per 1,000 in 1986, increased to 8.52 per 1,000 in 2000, maintained at 8.30 per 1,000 in 2003, downed to 0.77 per 1,000 in 2007. In Sichuan Province, the epilepsy prevalence was 2.65 per 1,000 in 1987 and 2.91 per 1,000 in 1993, dropped to 0.47 per 1,000 in 2005, and climbed up to 1.85 per 1,000 in 2009. In Hunan Province, the epilepsy prevalence was 4.18 per 1,000 in 1983, increased to 5.16 per 1,000 in 1985, and fell to around 1.28 per 1,000 during 1987 and 1996, but rose at 4.46 per 1,000 in 2010. In Tibet, the prevalence of epilepsy changed dramatically in the period of 1987 to 2009. It was 2.42 per 1,000 in 1987, 7.18 per 1,000 in 2003, 2.50 per 1,000 in 2006, 23.47 per 1,000 in 2008, and 4.05 per 1,000 in 2009. However, the dramatic difference of epilepsy prevalence over time might be partially caused by variable sample sizes, distinct sampling regions, diverse diagnostic criteria and even sampling bias in these studies conducted in different years.
Figure 3. Prevalence of epilepsy in 6 provincial regions over time, (A), Shandong, (B), Jiangsu, (C), Ningxia, (D), Sichuan, (E), Hunan, and (F), Tibet (Xizang Zizhiqu), respectively.
Possible risk factors of epilepsy within and outside the epilepsy belt
Table 2 and Figure 4 also showed the data of urbanization rate, GDP per capita, percentage of <15 years old and per capita medical insurance in 33 provincial regions. There was no significant difference of the urbanization rate, GDP per capita, medical insurance per capita, and percentage of <15 years old between regions in and outside the epilepsy belt (P > 0.05), and none of them was correlated with the regional epilepsy prevalence (P > 0.05).
Figure 4. The color-coded maps of possible risk factors for epilepsy in the 33 provincial regions with different color representing different rate. (A) Urbanization rates (%), (B) GDP per capita (/10,000 US Dollar), (C) percentage of <15 years old (%), (D) per capita medical insurance (/Yuan, RMB) in 33 provincial regions. There was no significant difference of the urbanization rate, GDP per capita, medical insurance per capita, and percentage of <15 years old between regions in and outside the epilepsy belt (P > 0.05), and none of them was correlated with the regional epilepsy prevalence (P > 0.05).
Discussion
It is estimated that there are over 70 million epilepsy patients in the world (2). The death risk of epilepsy patients is 2–3 times of the death risk of general population. In addition to the high mortality, epilepsy also induces disability, while great majority of patients with epilepsy are young patients, which bring severe burden to the families and society. Approximately 80% of epilepsy patients live in low-income and middle-income countries. In China, although the death caused by epilepsy has decreased by 34.8% from 1990 to 2010 (from 187,000 to 122,000), and the DALYs has also decreased from 1,723,100 to 1,597,400, the prevalence of life time epilepsy was found significantly higher at present than in the past (2.42 per 1,000 in 1990 v.s. 8.43 per 1,000 in 2015, in the 30–34 age group) (69).
Prevalence rate plays an important role in the secondary and tertiary prevention of diseases. The epilepsy prevalence is higher in China than in developed countries, and was found growing in the past decades, which indicates that it is necessary to improve the health service system in China (70). In this study, we extracted data from 60 studies providing data on the prevalence of epilepsy between 1978 and 2020 in 29 of 33 provincial regions of China. Our study showed that the overall prevalence of epilepsy in China was 1.68 per 1,000. Among the 29 provincial regions, 12 of them, including Heilongjiang, Shanxi, Tibet, Hubei, Henan, Jilin, Hebei, Beijing, Guangxi, Taiwan, Guizhou, and Hunan possessed higher epilepsy (3.32 per 1,000 in average) prevalence than the overall epilepsy prevalence.
In order to investigate the possible reasons of unbalanced epilepsy prevalence in difference regions of China and even the causes of the epilepsy belt, we surveyed the factors reported to be related with epilepsy prevalence, including poverty, young age and countryside (2). Surprisingly, there was no significant difference in urbanization rate, GDP per capita, medical insurance per capita or percentage of <15 years old between the regions with higher epilepsy prevalence and with lower epilepsy prevalence. And none of these factors was correlated with the regional epilepsy prevalence. As we all know, to the worldwide extent, the incidence of epilepsy is higher in children and adolescents than in adults. However, the epilepsy prevalence increases along with age grows, peaks at 25–35 age group and 45–50 age group, and declines after 55 (2). In this study, more specific age groups might lead to positive results, however, majority of those enrolled publications had no specific age groups. Moreover, in recent decades, since the growing population aging leads to increased incidence of cerebral vascular diseases and neurodegenerative disorders, the incidence of epilepsy is growing in elderly people (69), which might be one of the reasons that no differences of young age percentage was found between epilepsy belt and regions outside the belt. In some researches, epilepsy was found tending to affect poor population and rural area (71). However, the data of a large-scale epidemiological investigations conducted in 1980s in urban area of six cities and rural area of 21 provincial regions, revealed that the prevalence of epilepsy in rural area was 3.6 per 1,000, while the epilepsy prevalence in urban area was 4.4 per 1,000 (41), and in our study, data from the whole country sustained this result, the urbanization rate was not correlated with the regional epilepsy prevalence. The GDP per capita and medical insurance per capita, which could reflect the economics and medical conditions in one region, were assumed to be correlated with the regional prevalence of epilepsy, based on the previous researches (2, 71). However, the distinct results from our study provided new evidence to the study of risk factors of epilepsy.
Interestingly, 10 out of the 12 provincial regions constituting the epilepsy belt located along the division between the second step and the third step of China. The highest prevalence was found in Heilongjiang Province (8.08 per 1,000), which occupied the east side of the Daxing'an mountains. China's mainland consists of plains, basins, plateaus, foothills, and mountains, in which rugged plateaus, foothills and mountains form a topographic feature higher in the West and lower in the East like a three-step ladder. The highest step (first step) is formed by the Qinghai-Tibet Plateau at the average height of over 4,000 m, with the Kunlunshan range, Qilianshan range and Hengduan mountain chain as the division between the first and the second step. On the second step, there are large basins and plateaus, most of them are at the height of 1,000–2,000 meters. The second and the third step are divided by the Daxing'an range, Taihang range, Wu and Xuefeng Mountains. The third step is dotted with the lower mountains and foothills, with altitudes of 500–1,000 m (7). Beside of the height, the temperature, humidity (humidity, rainfall), sunshine time, percentage of ethnic minorities, housing area per capita, number of hospital beds per capita, number of doctors per capita, health expenditure, habits and customs, are diverse in these three steps (7). It might be possible that the unique features of the geographic conditions and of the population lived at the division of the second step and the third step contributed to the higher prevalence of epilepsy. The difference of height, temperature, sunshine time, and socio-cultural characteristics mentioned above should be enrolled in during future researches.
Several limitations should be emphasized when interpreting the results of this study. First, retrieving epilepsy prevalence rates from multiple epidemiological surveys may generate bias because of discrepancies in sampling and other methodology. The geographical distribution of the sampling sites of the 60 enrolled studies was uneven. Although the population density in China is uneven, much denser in south China than north China (eg, >700/km2 in Jiangsu vs. <10/km2 in Xinjiang) (6), the samples size/population was lower in the less populated regions of northern China than in southern China and, in particular, there was no sampling in the Inner Mongolia. Besides, some of the researches focused on urban regions and some of them surveyed in cities covering urban and rural areas, others only investigated in the rural area. In addition, the enrolled studies were conducted during 1978 and 2020, not a specific time point. As the data showed, epilepsy prevalence may change over time in a given region. For instance, in Hunan, the prevalence of epilepsy changed dramatically in the period of 1983 to 2010. It was 4.18 per 1,000 in 1983, 5.16 per 1,000 in 1985, 1.28 per 1,000 in 1987, 1.20 per 1,000 in 1992, 1.68 per 1,000 in 1996, and 4.46 per 1,000 in 2010 (23, 27, 28, 39, 42, 63). However, the dramatic difference of epilepsy prevalence over time might be partially caused by variable sample sizes, distinct sampling regions, diverse diagnostic criteria and even sampling bias in these studies conducted in different years. What's more, some researches focused on a specific age group such as <14 years old (30, 33), and some researches only surveyed a specific epilepsy type (11, 52), both could lead to bias. And majority of the enrolled researches did not include specific age groups, only mentioning all age range or children, based on these data, it is impossible to investigate the relationship between specific age groups and epilepsy prevalence.
Conclusions
In conclusion, we have identified an epilepsy belt of high prevalence across 12 provincial regions located along the geographical division between the second step and the third step of China. The underlying reasons forming this epilepsy belt should be investigated further for population-based epilepsy prevention.
Data availability statement
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.
Ethics statement
Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the participants' legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.
Author contributions
LW and ZY: data curation, writing—original draft preparation, and funding acquisition. YL: data curation, software, and visualization. ML: project administration and visualization. SL: formal analysis. HM: validation. ZQ: formal analysis, methodology, and funding acquisition. YJ: conceptualization, supervision, writing—review and editing, and funding acquisition. All authors read and approved the final manuscript.
Funding
This study was supported by the National Natural Science Foundation of China [grant numbers: 81471181, 81870933, and 81701471], the Guangdong Provincial Medical Science and Technology Research Fund [A2021406], the Guangzhou Medical and Health Science and Technology Project [20191A011083 and 20211A011080], the Science and Technology Planning Project of Panyu District [2019-Z04-11], and the Opening Lab Program of Guangzhou Medical University [0506308]. The funding sources had no involvement in the design of the study and collection, analysis, interpretation of data, and in writing the manuscript.
Acknowledgments
We thank Ying Pan for helping us to achieve several enrolled publications.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Abbreviations
YLDs, years lived with disability; DALYs, disability-adjusted life-years; CNKI, China National Knowledge Infrastructure; WHO, World Health Organization; ILAE, International League against Epilepsy.
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Keywords: China, epilepsy, prevalence, epidemiology, risk factors
Citation: Wu L, Ye Z, Li Y, Luo M, Li S, Mi H, Qiu Z and Jiang Y (2022) Is there an epilepsy belt of high prevalence rate in China? Front. Neurol. 13:994305. doi: 10.3389/fneur.2022.994305
Received: 14 July 2022; Accepted: 30 September 2022;
Published: 19 October 2022.
Edited by:
Yuping Wang, Capital Medical University, ChinaReviewed by:
Vaishnav Krishnan, Baylor College of Medicine, United StatesGagandeep Singh, North Dakota State University, United States
Copyright © 2022 Wu, Ye, Li, Luo, Li, Mi, Qiu and Jiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Zhihua Qiu, zhihuaqiu421@163.com; Yongjun Jiang, jiangyjnju@gmail.com
†These authors have contributed equally to this work
‡ORCID: Li Wu orcid.org/0000-0003-0210-6928
Yongjun Jiang orcid.org/0000-0003-2405-7370