Journal of Peking University (Health Sciences) ›› 2020, Vol. 52 ›› Issue (3): 521-526. doi: 10.19723/j.issn.1671-167X.2020.03.019

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Calculation of the prevalence of progressive muscular atrophy among adults in China based on urban medical insurance data from 15 provinces

Lu XU1,Lu CHEN2,Dong-sheng FAN2,Jing-nan FENG1,Li-li LIU1,Si-yan ZHAN1,3,Sheng-feng WANG1,()   

  1. 1. Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
    2. Department of Neurology, Peking University Third Hospital, Beijing 100191, China
    3. Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, China
  • Received:2020-02-05 Online:2020-06-18 Published:2020-06-30
  • Contact: Sheng-feng WANG E-mail:shengfeng1984@126.com

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Abstract:

Objective: To analyze the characteristics of patients with progressive muscular atrophy (PMA) and calculate the prevalence of PMA in China in 2016.Methods: A retrospective analysis based on China’s urban employee basic medical insurance data and the urban residence basic medical insu-rance data from January 1, 2016 to December 31, 2016 was carried out. Children under 18 years old were excluded. Patients with progressive muscular atrophy were identified by disease names and codes. Subgroup analyses by gender, region and age were carried out to calculate the gender-specific, region-specific and age-specific prevalences. Age-adjusted national prevalence was estimated based on 2010 Chinese census data. Sensitivity analyses were done by only considering the observed cases and by excluding the top 10% provinces regarding the missing rate of diagnostic information, respectively.Results: A total of 996.09 million person-years were included in this study, with 518.41 million person-years in males and 477.67 million person-years in females. The age and gender distribution of the study population was similar to that of the 2010 Chinese census data, therefore the study population was nationally representative. The prevalence of PMA in China in 2016 was 0.28 per 100 000 person-years (95%CI: 0.24-0.33), with 0.21 per 100 000 person-years (95%CI: 0.16-0.26) and 0.35 per 100 000 person-years (95%CI: 0.28-0.42) for females and males, respectively. Regional disparity existed in the Chinese PMA prevalence, with the lowest prevalence in Southwest region (0.11 per 100 000 person-years, 95%CI: 0.07-0.15) and the highest prevalence in Northwest region (3.47 per 100 000 person-years, 95%CI: 0.80-7.99). Age trend in the PMA prevalence was not obvious, but the prevalence among those aged 70 years and older was relatively higher. The age-adjusted prevalence based on 2010 Chinese census data was 0.29 per 100 000 person-years (95%CI: 0.27-0.31). The national prevalences calculated by only considering the observed cases and by excluding the top 10% provinces regar-ding the missing rate of diagnostic information were 0.17 per 100 000 person-years (95%CI: 0.14-0.20) and 0.24 per 100 000 person-years (95%CI: 0.20-0.28), respectively.Conclusion: This study is to calculate the prevalence of PMA among adults in urban China, which can provide basic statistics for the enactment of PMA related medical policies, and clues for the studies on the mechanisms of PMA.

Key words: Progressive muscular atrophy, Prevalence, Medical insurance

CLC Number: 

  • R195.4

Table 1

Person-years of urban population in 15 provinces of China in 2016"

Items Total (×106) Male (×106) Female (×106)
Person-years 996.09a 518.41 477.67
Age group/years, n (%)
18-29 283.82 (28.49) 149.75 (28.89) 134.08 (28.07)
30-39 190.23 (19.10) 99.21 (19.14) 91.02 (19.05)
40-49 204.55 (20.54) 105.55 (20.36) 98.99 (20.72)
50-59 143.84 (14.44) 76.18 (14.69) 67.66 (14.16)
60-69 97.81 (9.82) 50.81 (9.80) 47.01 (9.84)
70-79 50.77 (5.10) 25.58 (4.93) 25.19 (5.27)
≥80 25.08 (2.52) 11.34 (2.19) 13.74 (2.88)
Areab, n (%)
East 421.35 (43.07) 217.51 (42.71) 203.83 (43.46)
North 40.18 (4.11) 20.12 (3.95) 20.05 (4.27)
Northeast 117.13 (11.97) 58.61 (11.51) 58.52 (12.48)
Northwest 20.18 (2.06) 10.70 (2.10) 9.48 (2.02)
Southcentral 252.14 (25.77) 135.96 (26.70) 116.18 (24.77)
Southwest 127.35 (13.02) 66.36 (13.03) 60.99 (13.00)

Figure 1

Pyramid of population proportion by age and gender in 2010 Chinese census data (A) and in this study (B)"

Table 2

Characteristics of urban patients with progressive muscular atrophy in 15 provinces of China in 2016"

Characteristic Total Male Female Statistic* P value
n 131 70 61
Age/years, x?±s 46.21±16.86 49.20±17.31 42.77±15.77 -2.21 0.029
Age group/years, n(%) 7.07 0.289
18-29 26 (19.85) 11 (15.71) 15 (24.59)
30-39 22 (16.79) 11 (15.71) 11 (18.03)
40-49 27 (20.61) 13 (18.57) 14 (22.95)
50-59 26 (19.85) 13 (18.57) 13 (21.31)
60-69 16 (12.21) 12 (17.14) 4 (6.56)
70-79 12 (9.16) 9 (12.86) 3 (4.92)
≥80 2 (1.53) 1 (1.43) 1 (1.64)
Area, n (%) 7.82 0.157
East 15 (11.45) 8 (11.43) 7 (11.48)
North 3 (2.29) 3 (4.29) 0 (0)
Northeast 3 (2.29) 0 (0) 3 (4.92)
Northwest 2 (1.53) 1 (1.43) 1 (1.64)
Southcentral 106 (80.92) 56 (80.00) 50 (81.97)
Southwest 2 (1.53) 2 (2.86) 0 (0)

Table 3

The prevalence of progressive muscular atrophy among adults by gender, area, and age group in urban China in 2016 (/100 000 person-years)"

Items Prevalence (95%CI) P*
Gender <0.001
Male 0.35 (0.28-0.42)
Female 0.21 (0.16-0.26)
Area <0.001
East 0.22 (0.17-0.28)
North 0.65 (0.34-1.05)
Northeast 0.35 (0.18-0.58)
Northwest 3.47 (0.80-7.99)
Southcentral 0.38 (0.29-0.48)
Southwest 0.11 (0.07-0.15)
Age group/years 0.222
18-29 0.31 (0.17-0.49)
30-34 0.35 (0.18-0.57)
35-39 0.31 (0.16-0.51)
40-44 0.26 (0.14-0.41)
45-49 0.23 (0.12-0.37)
50-54 0.22 (0.12-0.34)
55-59 0.22 (0.12-0.35)
60-64 0.22 (0.12-0.36)
65-69 0.26 (0.14-0.41)
70-74 0.41 (0.21-0.67)
75-84 0.41 (0.23-0.64)
≥85 0.45 (0.15-0.91)

Figure 2

The age trend of the prevalence of progressive muscular atrophy among adults in urban China in 2016"

[1] Liewluck T, Saperstein DS. Progressive muscular atrophy[J]. Neurol Clin, 2015,33(4):761-773.
[2] Fowler WS, Miller RD, Mulder DW, et al. Exertional dyspnea: a primary complaint in unusual cases of progressive muscular atrophy and amyotrophic lateral sclerosis[J]. Ann Intern Med, 1957,46(1):119-125.
pmid: 13395221
[3] Logroscino G, Piccininni M, Marin B, et al. Global, regional, and national burden of motor neuron diseases 1990—2016: a systematic analysis for the Global Burden of Disease Study 2016[J]. Lancet Neurol, 2018,17(12):1083-1097.
[4] Xu L, Liu T, Liu L, et al. Global variation in prevalence and incidence of amyotrophic lateral sclerosis: a systematic review and meta-analysis[J]. J Neurol, 2020,267(4):944-953.
[5] Pinho AC, Goncalves E. Are amyotrophic lateral sclerosis caregi-vers at higher risk for health problems?[J]. Acta Med Port, 2016,29(1):56-62.
pmid: 26926900
[6] Tsai CP, Wang KC, Hwang CS, et al. Incidence, prevalence, and medical expenditures of classical amyotrophic lateral sclerosis in Taiwan, 1999—2008[J]. J Formos Med Assoc, 2015,114(7):612-619.
[7] Riku Y, Atsuta N, Yoshida M, et al. Differential motor neuron involvement in progressive muscular atrophy: a comparative study with amyotrophic lateral sclerosis[J]. BMJ Open, 2014,4(5):e005213.
[8] Kim WK, Liu X, Sandner J, et al. Study of 962 patients indicates progressive muscular atrophy is a form of ALS[J]. Neurology, 2009,73(20):1686-1692.
pmid: 19917992
[9] 王胜锋, 詹思延, 许璐, 等. 基于医保数据的单病种诊断信息快速结构化方法: 中国, CN109344250A [P]. 2019-02-15.
[10] Xu L, Chen L, Wang S, et al. Incidence and prevalence of amyotrophic lateral sclerosis in urban China: a national population-based study[J]. J Neurol Neurosurg Psychiatry, 2020,91(5):520-525.
pmid: 32139654
[11] Noubiap 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[J]. Lancet Glob Health, 2019,7(4):e448-e460.
[12] Leigh PN, Ray-Chaudhuri K. Motor neuron disease[J]. J Neurol Neurosurg Psychiatry, 1994,57(8):886-896.
pmid: 8057109
[13] Chio A, Brignolio F, Leone M, et al. A survival analysis of 155 cases of progressive muscular atrophy[J]. Acta Neurol Scand, 1985,72(4):407-413.
[14] Maragakis NJ. Motor neuron disease: progressive muscular atrophy in the ALS spectrum[J]. Nat Rev Neurol, 2010,6(4):187-188.
pmid: 20379201
[15] Marin B, Boumediene F, Logroscino G, et al. Variation in worldwide incidence of amyotrophic lateral sclerosis: a meta-analysis[J]. Int J Epidemiol, 2017,46(1):57-74.
[16] 邢志宏, 叶植材. 中国统计年鉴 [M]. 北京: 中国统计出版社, 2017: 31.
[17] Cui F, Liu M, Chen Y, et al. Epidemiological characteristics of motor neuron disease in Chinese patients[J]. Acta Neurol Scand, 2014,130(2):111-117.
[18] Wicks P, Abrahams S, Leigh PN, et al. Absence of cognitive, behavioral, or emotional dysfunction in progressive muscular atrophy[J]. Neurology, 2006,67(9):1718-1719.
[19] Chen L, Zhang B, Chen R, et al. Natural history and clinical features of sporadic amyotrophic lateral sclerosis in China[J]. J Neurol Neurosurg Psychiatry, 2015,86(10):1075-1081.
pmid: 26124198
[20] Smoyer-Tomic KE, Amato AA, Fernandes AW. Incidence and prevalence of idiopathic inflammatory myopathies among commercially insured, medicare supplemental insured, and medicaid enrolled populations: an administrative claims analysis[J]. BMC Musculoskelet Disord, 2012,13:103.
[21] Ki M, Choi HY, Kim KA, et al. Incidence, prevalence and complications of Budd-Chiari syndrome in South Korea: a nationwide, population-based study[J]. Liver Int, 2016,36(7):1067-1073.
[22] Rhee C, Dantes R, Epstein L, et al. Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009—2014[J]. JAMA, 2017,318(13):1241-1249.
doi: 10.1001/jama.2017.13836 pmid: 28903154
[23] Donnachie E, Schneider A, Mehring M, et al. Incidence of irritable bowel syndrome and chronic fatigue following GI infection: a population-level study using routinely collected claims data[J]. Gut, 2018,67(6):1078-1086.
pmid: 28601847
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