Urban prevalence of multiple sclerosis in China: A population-based study in six provinces
Lu Xu
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
Search for more papers by this authorLu Chen
Department of Neurology, Peking University Third Hospital, Beijing, China
Search for more papers by this authorCorresponding Author
Shengfeng Wang
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
Correspondence
Shengfeng Wang and Siyan Zhan, Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
Emails: [email protected] (S.W.); [email protected] (S.Z.)
Dongsheng Fan, Department of Neurology, Peking University Third Hospital, 49 Huayuan North Road, Haidian District, Beijing 100191, China
Email: [email protected]
Search for more papers by this authorJingnan Feng
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
Search for more papers by this authorLili Liu
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
Search for more papers by this authorGuozhen Liu
Peking University Health Information Technology Co. Ltd, Beijing, China
Search for more papers by this authorJinxi Wang
Beijing Healthcom Data Technology Co. Ltd, Beijing, China
Search for more papers by this authorCorresponding Author
Siyan Zhan
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, China
Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing, China
Correspondence
Shengfeng Wang and Siyan Zhan, Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
Emails: [email protected] (S.W.); [email protected] (S.Z.)
Dongsheng Fan, Department of Neurology, Peking University Third Hospital, 49 Huayuan North Road, Haidian District, Beijing 100191, China
Email: [email protected]
Search for more papers by this authorCorresponding Author
Dongsheng Fan
Department of Neurology, Peking University Third Hospital, Beijing, China
Correspondence
Shengfeng Wang and Siyan Zhan, Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
Emails: [email protected] (S.W.); [email protected] (S.Z.)
Dongsheng Fan, Department of Neurology, Peking University Third Hospital, 49 Huayuan North Road, Haidian District, Beijing 100191, China
Email: [email protected]
Search for more papers by this authorLu Xu
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
Search for more papers by this authorLu Chen
Department of Neurology, Peking University Third Hospital, Beijing, China
Search for more papers by this authorCorresponding Author
Shengfeng Wang
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
Correspondence
Shengfeng Wang and Siyan Zhan, Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
Emails: [email protected] (S.W.); [email protected] (S.Z.)
Dongsheng Fan, Department of Neurology, Peking University Third Hospital, 49 Huayuan North Road, Haidian District, Beijing 100191, China
Email: [email protected]
Search for more papers by this authorJingnan Feng
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
Search for more papers by this authorLili Liu
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
Search for more papers by this authorGuozhen Liu
Peking University Health Information Technology Co. Ltd, Beijing, China
Search for more papers by this authorJinxi Wang
Beijing Healthcom Data Technology Co. Ltd, Beijing, China
Search for more papers by this authorCorresponding Author
Siyan Zhan
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, China
Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing, China
Correspondence
Shengfeng Wang and Siyan Zhan, Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
Emails: [email protected] (S.W.); [email protected] (S.Z.)
Dongsheng Fan, Department of Neurology, Peking University Third Hospital, 49 Huayuan North Road, Haidian District, Beijing 100191, China
Email: [email protected]
Search for more papers by this authorCorresponding Author
Dongsheng Fan
Department of Neurology, Peking University Third Hospital, Beijing, China
Correspondence
Shengfeng Wang and Siyan Zhan, Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China
Emails: [email protected] (S.W.); [email protected] (S.Z.)
Dongsheng Fan, Department of Neurology, Peking University Third Hospital, 49 Huayuan North Road, Haidian District, Beijing 100191, China
Email: [email protected]
Search for more papers by this authorLu Xu and Lu Chen are joint first authors.
Funding information
This work was supported by the National Natural Science Foundation (grant numbers 91646107, 81701248 and 81873784).
Abstract
Background and purpose
Multiple sclerosis (MS) is a rare neurological disease addressed by only few epidemiological studies in China. This population-based study aimed to estimate the prevalence of MS in China by using national medical insurance databases.
Methods
Data from the Urban Employee Basic Medical Insurance database and the Urban Residence Basic Medical Insurance database, which were collected during 2012 to 2016 and included approximately 0.20 billion residents in six provinces, were used in this population-based study. The prevalent patients with MS were identified via diagnostic text or disease codes.
Results
The crude prevalence in 2016 was 2.44 per 100,000 population (95% confidence interval (CI) 2.18–2.72), with the prevalence in females being higher than that in males. The standardized prevalence (based on 2010 Chinese census data) was 2.29 (95% CI 2.21–2.38). The prevalence in both sexes in 2016 increased up to the age range of 30–34 years. Subsequently, the female prevalence declined with increasing age, but male prevalence stabilized with increasing age. During the 5-year time period, prevalence ranged from 2.32 (95% CI 2.06–2.60) in 2015 to 2.91 (95% CI 2.39–3.47) in 2012.
Conclusions
The prevalence of MS in China was lower than that in Europe and North America. The temporal trend of prevalence in China was also observed to be stable. As the first prevalence study of MS in mainland China, this population-based study can provide useful information for worldwide healthcare services and prevention of MS.
CONFLICT OF INTEREST
None declared.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available upon request from the corresponding author. The data are not publicly available, due to privacy or ethical restrictions.
Supporting Information
| Filename | Description |
|---|---|
| ene14764-sup-0001-FileS1.docxWord document, 21.4 KB | File S1 |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
REFERENCES
- 1Kalb R, Feinstein A, Rohrig A, Sankary L, Willis A. Depression and suicidality in multiple sclerosis: red flags, management strategies, and ethical considerations. Curr Neurol Neurosci Rep. 2019; 19: 77.
- 2Leray E, Moreau T, Fromont A, Edan G. Epidemiology of multiple sclerosis. Rev Neurol (Paris). 2016; 172: 3-13.
- 3Kingwell E, Marriott JJ, Jette N, et al. Incidence and prevalence of multiple sclerosis in Europe: a systematic review. BMC Neurol. 2013; 13: 128.
- 4Zrzavy T, Kollaritsch H, Rommer PS, et al. Vaccination in multiple sclerosis: friend or foe? Front Immunol. 2019; 10: 1883.
- 5Bishop M, Rumrill PD. Multiple sclerosis: etiology, symptoms, incidence and prevalence, and implications for community living and employment. Work. 2015; 52: 725-734.
- 6Eskandarieh S, Heydarpour P, Minagar A, Pourmand S, Sahraian MA. Multiple sclerosis epidemiology in East Asia, South East Asia and South Asia: a systematic review. Neuroepidemiology. 2016; 46: 209-221.
- 7Nguyen AL, Eastaugh A, van der Walt A, Jokubaitis VG. Pregnancy and multiple sclerosis: clinical effects across the lifespan. Autoimmun Rev. 2019; 18:102360.
- 8Feinstein A, Pavisian B. Multiple sclerosis and suicide. Mult Scler. 2017; 23: 923-927.
- 9 London: Multiple Sclerosis International Federation. Atlas of MS 2013: Mapping Multiple Sclerosis Around the World. 2013. http://www.msif.org/about-ms/publications-and-resources/. Accessed on 22 January 2020.
- 10Campbell JA, Simpson S, Ahmad H, Taylor BV, van der Mei I, Palmer AJ. Change in multiple sclerosis prevalence over time in Australia 2010–2017 utilising disease-modifying therapy prescription data. Mult scler. 2019; 26(11): 1315-1328.
- 11Koch-Henriksen N, Sørensen PS. The changing demographic pattern of multiple sclerosis epidemiology. Lancet Neurol. 2010; 9: 520-532.
- 12Lai CH, Tseng HF. Population-based epidemiological study of neurological diseases in Taiwan: I. Creutzfeldt-Jakob disease and multiple sclerosis. Neuroepidemiology. 2009; 33: 247-253.
- 13Hou JB, Zhang ZX. Prevalence of multiple sclerosis: a door-to-door survey in Lan Cang La Hu Zu Autonomous County, Yunnan Province of China. Neuroepidemiology. 1992; 11: 52.
- 14Cheng Q, Miao L, Zhang J, et al. A population-based survey of multiple sclerosis in Shanghai, China. Neurology. 2007; 68: 1495-1500.
- 15Shan L, Wu Q, Liu C, et al. Perceived challenges to achieving universal health coverage: a cross-sectional survey of social health insurance managers/administrators in China. BMJ Open. 2017; 7:e014425.
- 16Yang Y, Zhang J, Du F, Montgomery W, Li H, Flynn JA. Real world evidence in mainland China: experience with the use of health care claims data. Value Health. 2014; 17: A728.
- 17Xu L, Chen L, Wang S, et al. Incidence and prevalence of amyotrophic lateral sclerosis in urban China: a national population-based study. J Neurol Neurosurg Psychiatry. 2020; 91: 520-525.
- 18Wallin MT, Culpepper WJ, Campbell JD, et al. The prevalence of MS in the United States: a population-based estimate using health claims data. Neurology. 2019; 92: e1029-e1040.
- 19Marrie RA, O'Mahony J, Maxwell C, et al. Incidence and prevalence of MS in children: a population-based study in Ontario, Canada. Neurology. 2018; 91: e1579-e1590.
- 20Noubiap JJ, Bigna JJ, Nansseu JR, et al. Prevalence of dyslipidaemia among adults in Africa: a systematic review and meta-analysis. Lancet Glob Health. 2018; 6: e998-e1007.
- 21Noubiap JJ, Nansseu JR, Nyaga UF, et al. Global prevalence of diabetes in active tuberculosis: a systematic review and meta-analysis of data from 2.3 million patients with tuberculosis. Lancet Glob Health. 2019; 7: e448-e460.
- 22Browne P, Chandraratna D, Angood C, et al. Atlas of multiple sclerosis 2013: a growing global problem with widespread inequity. Neurology. 2014; 83: 1022-1024.
- 23Kira J. Multiple sclerosis in the Japanese population. Lancet Neurol. 2003; 2: 117-127.
- 24Liu G, Zhang F, Hu Y, et al. Multiple sclerosis risk pathways differ in Caucasian and Chinese populations. J Neuroimmunol. 2017; 307: 63-68.
- 25Navaderi M, Rajaei S, Rahimirad S, et al. Identification of Multiple Sclerosis key genetic factors through multi-staged data mining. Mult Scler Relat Disord. 2019; 39:101446.
- 26Pandit L, Ban M, Beecham AH, et al. European multiple sclerosis risk variants in the south Asian population. Mult Scler. 2016; 22: 1536-1540.
- 27Trojano M, Lucchese G, Graziano G, et al. Geographical variations in sex ratio trends over time in multiple sclerosis. PLoS ONE. 2012; 7:e48078.
- 28Bove R, Chitnis T. Sexual disparities in the incidence and course of MS. Clin Immunol. 2013; 149: 201-210.
- 29Golden LC, Voskuhl R. The importance of studying sex differences in disease: the example of multiple sclerosis. J Neurosci Res. 2017; 95: 633-643.
- 30Kotzamani D, Panou T, Mastorodemos V, et al. Rising incidence of multiple sclerosis in females associated with urbanization. Neurology. 2012; 78: 1728-1735.
- 31Dunn SE, Gunde E, Lee H. Sex-based differences in multiple sclerosis (MS): part II: rising incidence of multiple sclerosis in women and the vulnerability of men to progression of this disease. Curr Top Behav Neurosci. 2015; 26: 57-86.
- 32Magyari M. Gender differences in multiple sclerosis epidemiology and treatment response. Dan Med J. 2016; 63: B5212.
- 33Hunt K, Adamson J, Galdas P. The Palgrave Handbook of Gender and Healthcare. London, UK: Palgrave Macmillan; 2010.
- 34Yan S, Xu F, Yang C, et al. Demographic differences in sun protection beliefs and behavior: a community-based study in Shanghai, China. Int J Environ Res Public Health. 2015; 12: 3232-3245.
- 35Cheng S, Lian S, Hao Y, et al. Sun-exposure knowledge and protection behavior in a North Chinese population: a questionnaire-based study. Photodermatol Photoimmunol Photomed. 2010; 26: 177-181.
- 36Yan X, Zhang N, Cheng S, Wang Z, Qin Y. Gender differences in vitamin D status in China. Med Sci Monit. 2019; 25: 7094-7099.
- 37Kragt J, van Amerongen B, Killestein J, et al. Higher levels of 25-hydroxyvitamin D are associated with a lower incidence of multiple sclerosis only in women. Mult Scler. 2009; 15: 9-15.
- 38Saraff V, Shaw N. Sunshine and vitamin D. Arch Dis Child. 2016; 101: 190-192.
- 39Arya R, Antonisamy B, Kumar S. Sample size estimation in prevalence studies. Indian J Pediatr. 2012; 79: 1482-1488.
- 40Lilyana A, Erica R, Sarah J, Juanjuan Z, Lihua L. Multiple sclerosis mortality by race/ethnicity, age, sex, and time period in the United States, 1999–2015. Neuroepidemiology. 2018; 50: 35-40.
- 41Asgari N, Lillevang ST, Skejoe HPB, Kyvik KO. Epidemiology of neuromyelitis optica spectrum disorder in Denmark (1998-2008, 2007-2014). Brain Behav. 2019; 9:e01338.
- 42Weber MS, Derfuss T, Metz I, Bruck W. Defining distinct features of anti-MOG antibody associated central nervous system demyelination. Ther Adv Neurol Disord. 2018; 11: 1756286418762083.
- 43Jarius S, Wildemann B. The history of neuromyelitis optica. Part 2: ‘Spinal amaurosis’, or how it all began. J Neuroinflammation. 2019; 16: 280.
- 44Cobo-Calvo A, Marignier R. MOG-antibody-associated disease is different from MS and NMO and should be considered as a distinct disease entity - No. Mult Scler. 2019; 26(3): 274-276.
- 45Donnachie E, Schneider A, Mehring M, Enck P. Incidence of irritable bowel syndrome and chronic fatigue following GI infection: a population-level study using routinely collected claims data. Gut. 2018; 67: 1078-1086.
- 46Rhee C, Dantes R, Epstein L, et al. Incidence and trends of sepsis in us hospitals using clinical vs claims data, 2009-2014. JAMA. 2017; 318: 1241-1249.
- 47Wendt JK, Symanski E, Du XL. Estimation of asthma incidence among low-income children in Texas: a novel approach using Medicaid claims data. Am J Epidemiol. 2012; 176: 744-750.
