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With the development of science and technology and the process of industrialization, the working conditions of workers have changed greatly. During their work, workers frequently undergo local muscle tension such as repetitive operation, poor working posture, excessive force load, continuous muscle tension, vibration contact, and other health effects caused by adverse working conditions. Work-related musculoskeletal disorders (WMSDs) caused by adverse ergonomics are becoming increasingly prominent. As early as 2002, the International Labor Organization (ILO) added WMSDs in the international list of occupational diseases and refined it in the latest edition of occupational diseases catalogue approved in 2010, including seven categories and an open clause (1). Currently, WMSDs are not included in the list of statutory occupational diseases in China. Rather, it is only perceived as work-related diseases, so there is no legal basis for preventing and controlling WMSDs among occupational groups. In 2019, China put forward in the Healthy China Action (2019–2030) that the prevention and control of WMSDs should be included in the national health action goal. Therefore, a large sample of people in key industries in different regions of China were investigated and studied to determine the prevalence and distribution characteristics of WMSDs in key industries of China and explore related epidemiological characteristics.
The scope of this study covers seven regions of North, East, Central, South, Southwest, Northwest and Northeast China. Selection of key industries is based on representative industries closely related to WMSDs, i.e., involving 15 industries such as automobile manufacturing, footwear industry, biological medicine manufacturing, electronic equipment manufacturing, ship and related equipment manufacturing, petrochemical industry, construction industry, furniture manufacturing, coal mining and cleaning industry, animal husbandry, medical staff, automobile 4S shops, vegetable greenhouses, civil aviation flight attendants, and toy manufacturing. In this study, a cluster sampling method was adopted, and all workers on duty who met the inclusion criteria were selected as research objects from the representative enterprises in the key industries and above areas. The inclusion criteria was workers with more than one year’s service, and the exclusion criteria was congenital spinal deformity and non-WMSD patients due to trauma, infectious diseases, and malignant tumors.
In the study, the epidemiological cross-sectional survey method and the electronic questionnaire system of Chinese version of musculoskeletal disorders questionnaire were used to investigate the prevalence of WMSDs among occupational groups in key industries in different regions of China. This electronic questionnaire system was based on Nordic Musculoskeletal Questionnaires (NMQ) (2), and after proper modification, the adapted NMQ proved to have good reliability and validity for use for Chinese occupational groups. The criteria of the US National Institute for Occupational Safety and Health (NIOSH) for musculoskeletal injury was used to determine WMSDs (3). The survey was conducted by an investigator using face-to-face survey on N respondents, and the respondents answered questions online by mobile phone or by tablet after scanning Quick Response (QR) codes. Up to now, 57,501 valid questionnaires have been received, and the effective rate of questionnaires was 100%. There were 37,240 male workers and 20,261 female workers. The age of the investigated population was (32.3±9.2) years and the length of service was (7.5±7.2) years.
The standardized prevalence rate of WMSDs among the population in key industries in China was 41.2% (all patients suffering from WMSDS at any position are regarded as one patient). The standardized prevalence rate of WMSDs varied from 7.3% to 24.8%. The 3 parts with the highest prevalence were the neck (24.8%), shoulders (20.8%), and lower back (16.8%). Female workers had 1.5 times the risk of WMSDs compared to male workers. A significant difference in the prevalence of WMSDs was observed between different age groups and different working age groups (P<0.05). The prevalence rate of WMSDs increased gradually and decreased with age, and the highest prevalence rate was between 35 and 45 years old. The prevalence of WMSDs increased with increased length of service. Regular physical exercise could reduce the risk of suffering from WMSDs. The risk of neck, shoulders, and lower back of people with different demographic characteristics was shown in Table 1.
Characteristic Number Any body part Neck Shoulders Lower back No. of cases Rate, % OR (95%CI) No. of cases OR (95%CI) No. of cases OR (95%CI) No. of cases OR (95%CI) Gender Male 37,240 14,057 37.7 1 7,774 1 6,419 1 5,514 1 Female 20,261 9,612 47.4 1.5 (1.4−1.5) * 6,713 1.9 (1.8−2.0) * 5,647 1.9 (1.8−1.9) * 3,935 1.4 (1.3−1.5) * Age (years) <25 12,085 4,426 36.6 1 2,389 1 2,027 1 1,462 1 25– 26,139 11,196 42.8 1.3 (1.2−1.4) * 6,967 1.5 (1.4−1.6) * 5,741 1.4 (1.3−1.5) * 4,577 1.5 (1.4−1.6) * 35– 12,301 5,294 43.0 1.3 (1.2−1.4) * 3,486 1.6 (1.5−1.7) * 2,888 1.5 (1.4−1.6) * 2,238 1.6 (1.5−1.7) * 45– 5,802 2,271 39.1 1.1 (1.0−1.2) * 1,385 1.2 (1.2−1.4) * 1,187 1.3 (1.2−1.4) * 964 1.4 (1.3−1.6) * 55– 1,174 482 41.1 1.2 (1.1−1.4) * 260 1.2 (1.0−1.3) * 223 1.2 (1.0−1.4) * 208 1.6 (1.3−1.8) * Working age (years) <2 16,061 5,498 34.2 1 2,955 1 2,536 1 1,886 1 2– 12,072 4,989 41.3 1.3 (1.3−1.4) * 3,011 1.5 (1.4−1.6) * 2,509 1.4 (1.3−1.5) * 1,857 1.4 (1.3−1.5) * 4– 7,299 3,106 42.6 1.4 (1.3−1.5) * 1,966 1.6 (1.5−1.7) * 1,654 1.6 (1.5−1.7) * 1,292 1.6 (1.5−1.7) * 6– 9,717 4,361 44.9 1.6 (1.5−1.6) * 2,805 1.8 (1.7−1.9) * 2,302 1.7 (1.6−1.8) * 1,853 1.8 (1.7−1.9) * 8– 12,352 5,715 46.3 1.7 (1.6−1.7) * 3,750 1.9 (1.8−2.0) * 3,065 1.8 (1.7−1.9) * 2,561 2.0 (1.8−2.1) * Education Junior high school 15,369 5,543 36.1 1 3,230 1 2,815 1 2,225 1 Senior high school 21,901 8,636 39.4 1.2 (1.1−1.2) * 4,990 1.1 (1.1−1.2) * 4,174 1.1 (1.0−1.1) * 3,399 1.1 (1.0−1.2) * University degree 19,231 8,949 46.5 1.5 (1.5−1.6) * 5,841 1.6 (1.6−1.7) * 4,729 1.5 (1.4−1.5) * 3,626 1.4 (1.3−1.5) * Graduate degree 1,000 541 54.1 2.1 (1.8−2.4) * 426 2.8 (2.4−3.2) * 348 2.4 (2.1−2.7) * 199 1.5 (1.2−1.7) * BMI <18.5 6,006 2,459 40.9 1 1,487 1 1,217 1 908 1 18.5– 39,328 16,130 41.0 1.0 (0.9−1.1) 9,973 1.0 (0.9−1.1) 8,389 1.1 (0.9−1.1) 6,414 1.1 (1.0−1.2) * 25– 12,167 5,080 41.8 1.0 (1.0−1.1) 3,027 1.0 (0.9−1.1) 2,460 1.0 (0.9−1.1) 2,127 1.2 (1.1−1.3) * Smoking No 36,527 15,496 42.4 1 9,895 1 8,227 1 6,074 1 Occasionally 10,111 3,616 35.8 0.8 (0.7−0.8) 2,049 0.7 (0. 6−0.7) * 1,708 0.7 (0.6−0.7) * 1,453 0.8 (0.8−0.9) * Frequently 10,863 4,557 41.9 1.0 (0.9−1.0) 2,543 0.8 (0. 8−0.9) * 2,131 0.8 (0.8−0.9) * 1,922 1.1 (1.0−1.1) * Sporting No 17,947 7,859 43.8 1 4,772 1 4,038 1 3,375 1 Occasionally 32,797 13,272 40.5 0.9 (0.8−0.9) * 8,147 0.9 (0.8−0.9) * 6,749 0.9 (0.8−0.9) * 5,116 0.8 (0.7−0.8) * Frequently 6,757 2,538 37.6 0.8 (0.7−0.8) * 1,568 0.8 (0.8−0.9) * 1,279 0.8 (0.7−0.8) * 958 0.7 (0.6−0.7) * Abbreviations: WMSDs=work-related musculoskeletal disorders; BMI=body mass index.
* P<0.05.Table 1. WMSD prevalence and risk for different demographic groups among key industries or occupational groups in China, 2018–2020.
The results showed statistical differences in the prevalence of WMSDs among occupational groups in different industries (P<0.05). The standardized prevalence rate of WMSDs in various industries from high to low was: flight attendants (55.7%), medical staff (54.2%), vegetable greenhouse (50.7%), toy manufacturing (49.0%), biopharmaceutical manufacturing (48.4%), automobile manufacturing (43.5%), electronic equipment manufacturing (40.4%), shipbuilding and related equipment manufacturing (40.1%), animal husbandry (39.7%), 4S automobile store (38.6%), coal mining and cleaning industry (38.4%), footwear industry (34.2%), furniture manufacturing (28.5%), construction industry (23.4%), and petrochemical industry (11.5%) (Table 2).
Industry Number (n) Any body part Neck Shoulders Upper back Lower back Elbows Wrists/Hands Hips/Thighs Knees Ankles/Feet n pi p' n pi p' n pi p' n pi p' n pi p' n pi p' n pi p' n pi p' n pi p' n pi p' Total 57,501 23,669 41.2 40.9 14,487 25.2 24.8 12,066 21.0 20.8 8,399 14.6 14.2 9,449 16.4 16.8 4,169 7.3 7.3 7,553 13.1 12.9 6,065 10.5 10.6 6,184 10.8 11.0 8,002 13.9 12.8 Automobile manufacturing 21,560 8,969 41.6 43.5 5,047 23.4 25.2 4,214 19.5 20.6 3,148 14.6 15.3 3,460 16.0 18.1 1,571 7.3 7.3 3,210 14.9 14.0 2,219 10.3 11.1 2,584 12.0 12.3 3,883 18.0 16.8 Electronic equipment manufacturing 8,116 3,158 38.9 40.4 2,060 25.4 25.2 1,758 21.7 22.4 1,156 14.2 14.2 1,129 13.9 13.9 515 6.3 6.4 889 11.0 10.9 701 8.6 8.4 572 7.0 8.1 800 9.9 10.9 Footwear industry 7,106 2,616 36.8 34.2 1,701 23.9 21.6 1,368 19.3 17.9 846 11.9 11.5 943 13.3 12.4 507 7.1 7.1 1,058 14.9 14.4 603 8.5 8.5 524 7.4 7.0 595 8.4 8.2 Medical staff 6,766 3,794 56.1 54.2 2,749 40.6 39.7 2,224 32.9 32.5 1,490 22.0 21.9 1,712 25.3 24.5 462 6.8 7.6 782 11.6 12.1 1,126 16.6 16.2 922 13.6 14.0 1,072 15.8 15.0 Furniture manufacturing 4,471 1,320 29.5 28.5 701 15.7 15.0 623 13.9 13.7 481 10.8 10.6 459 10.3 9.9 410 9.2 9.0 556 12.4 12.1 429 9.6 9.6 418 9.3 9.6 612 13.7 12.9 Shipbuilding and related equipment manufacturing 3,488 1,432 41.1 40.1 787 22.6 21.6 672 19.3 18.8 491 14.1 13.5 658 18.9 18.4 326 9.3 8.9 452 13.0 12.3 418 12.0 11.7 488 14.0 13.0 413 11.8 11.5 Coal mining and cleaning industry 1,500 586 39.1 38.4 362 24.1 23.7 311 20.7 20.2 223 14.9 13.0 259 17.3 15.6 133 8.9 7.6 168 11.2 10.2 188 12.5 11.6 244 16.3 15.0 200 13.3 0.1 Construction industry 1,379 332 24.1 23.4 134 9.7 9.5 147 10.7 10.5 102 7.4 7.1 165 12.0 11.6 55 4.0 3.9 89 6.5 5.9 63 4.6 4.6 50 3.6 3.5 63 4.6 4.5 Flight attendants 1,356 696 51.3 55.7 504 37.2 38.2 387 28.5 33.7 203 15.0 20.1 275 20.3 88.4 52 3.8 4.8 98 7.2 7.0 121 8.9 10.0 143 10.5 11.7 156 11.5 11.2 4S automobile store11 544 177 32.5 38.6 88 16.2 23.1 78 14.3 16.8 70 12.9 15.4 92 16.9 23.2 27 5.0 8.5 50 9.2 14.5 47 8.6 12.3 50 9.2 15.2 61 11.2 16.2 Toy manufacturing 333 167 50.2 49.0 119 35.7 34.2 116 34.8 31.6 84 25.2 24.2 91 27.3 25.3 71 21.3 20.1 97 29.1 28.3 55 16.5 14.9 63 18.9 18.9 64 19.2 19.4 Animal husbandry 246 96 39.0 39.7 62 25.2 27.3 41 16.7 17.7 20 8.1 8.6 64 26.0 27.1 19 7.7 8.3 47 19.1 20.6 23 9.3 10.1 35 14.2 14.2 15 6.1 6.3 Biopharmaceutical manufacturing 243 157 64.6 48.4 110 45.3 34.1 77 31.7 24.7 65 26.7 20.9 53 21.8 17.7 13 5.3 5.0 34 14.0 88.4 36 14.8 11.3 29 11.9 9.2 52 21.4 18.0 Vegetable greenhouse 243 147 60.5 50.7 51 21.0 18.7 43 17.7 15.0 16 6.6 4.5 79 32.5 27.1 5 2.1 1.5 16 6.6 4.2 30 12.3 10.3 57 23.5 16.6 13 5.3 3.7 Petrochemical industry 150 22 14.7 11.5 12 8.0 7.0 7 4.7 3.5 4 2.7 1.6 10 6.7 6.5 3 2.0 1.4 7 4.7 2.7 6 4.0 4.5 5 3.3 1.9 3 2.0 1.4 Chi-square test 1,336.7 1,525.7 992.4 550.4 P value 0 0 0 0 Note: Pi: Actual prevalence rate, P’: Standardized prevalence rate.
Abbreviation: WMSDs=work-related musculoskeletal disorders.Table 2. Prevalence of WMSDs in key industries or occupational groups in China, 2018–2020.
In this study, 56.5%–88.7% of the occupational population chose the pain scores for the neck, shoulders, upper back, lower back (waist), elbow, wrist/hand, hip/thigh, knee, ankle/foot, etc., as 0, which means no pain occurred. Therefore, this study used 10–90 percentile to express the distribution of pain scores. The results demonstrated that the pain scores of female workers were higher than those of male workers except for elbow and knee, which were statistically significant (P<0.05). The pain scores of different age groups, different working age groups, smoking history, and physical exercise habits were statistically significant (P<0.05) (Table 3).
Characteristic Neck Shoulders Upper back Lower back Elbows Wrists/Hands Hips/Thighs Knees Ankles/Feet M (Q10, Q90) Z/χ2 M (Q10, Q90) Z/χ2 M (Q10, Q90) Z/χ2 M (Q10, Q90) Z/χ2 M (Q10, Q90) Z/χ2 M (Q10, Q90) Z/χ2 M (Q10, Q90) Z/χ2 M (Q10, Q90) Z/χ2 M (Q10, Q90) Z/χ2 Gender Male 0(0, 6) −40.5** 0(0, 6) −37.8** 0(0, 5) −16.9** 0(0, 6) −15.8** 0(0, 2) −0.7 0(0, 5) −6.0** 0(0, 5) −10.6** 0(0, 5) −9.1 0(0, 6) −10.9** Female 3(0, 7) 0(0, 6) 0(0, 6) 0(0, 6) 0(0, 3) 0(0, 5) 0(0, 5) 0(0, 5) 0(0, 5) Age (years) <25 0(0, 6) 888.4** 0(0, 5) 619.5** 0(0, 5) 287.3** 0(0, 5) 684.8** 0(0, 0) 97.7** 0(0, 5) 38.3** 0(0, 4) 152.5** 0(0, 4) 182.4** 0(0, 6) 262.3** 25− 0(0, 6) 0(0, 6) 0(0, 6) 0(0, 6) 0(0, 2) 0(0, 5) 0(0, 5) 0(0, 5) 0(0, 6) 35− 0(0, 6) 0(0, 6) 0(0, 6) 0(0, 6) 0(0, 4) 0(0, 5) 0(0, 5) 0(0, 5) 0(0, 5) 45− 0(0, 6) 0(0, 6) 0(0, 5) 0(0, 5) 0(0, 4) 0(0, 5) 0(0, 4) 0(0, 5) 0(0, 4) 55− 0(0, 6) 0(0, 6) 0(0, 5) 0(0, 5) 0(0, 1) 0(0, 4) 0(0, 4) 0(0, 5) 0(0, 4) Working age (years) <2 0(0, 6) 1740.3** 0(0, 5) 1225.6** 0(0, 5) 667.1** 0(0, 5) 1300.8** 0(0, 0) 86.9** 0(0, 5) 36.5** 0(0, 4) 343.5** 0(0, 4) 664.9** 0(0, 5) 102.2** 2− 0(0, 6) 0(0, 6) 0(0, 5) 0(0, 6) 0(0, 3) 0(0, 5) 0(0, 5) 0(0, 5) 0(0, 5) 4− 0(0, 6) 0(0, 6) 0(0, 6) 0(0, 6) 0(0, 2) 0(0, 5) 0(0, 5) 0(0, 5) 0(0, 5) 6− 0(0, 7) 0(0, 6) 0(0, 6) 0(0, 6) 0(0, 3) 0(0, 5) 0(0, 5) 0(0, 5) 0(0, 6) 8− 2(0, 7) 0(0, 6) 0(0, 6) 0(0, 6) 0(0, 4) 0(0, 5) 0(0, 5) 0(0, 6) 0(0, 6) BMI <18.5 0(0, 6) 6.4* 0(0, 6) 10.3** 0(0, 5) 15.5* 0(0, 6) 76.6** 0(0, 1) 8.4 0(0, 5) 2.5 0(0, 5) 3.6 0(0, 5) 49.2** 0(0, 5) 49.7** 18.5− 0(0, 6) 0(0, 6) 0(0, 5) 0(0, 6) 0(0, 3) 0(0, 5) 0(0, 5) 0(0, 5) 0(0, 5) 25− 0(0, 6) 0(0, 6) 0(0, 6 0(0, 6) 0(0, 3) 0(0, 5) 0(0, 5) 0(0, 5) 0(0, 6) Smoking No 0(0, 6) 421.9** 0(0, 6) 327.2** 0(0, 5) 102.3** 0(0, 6) 214.1** 0(0, 2) 38.3** 0(0, 5) 53.0** 0(0, 5) 62.9** 0(0, 5) 104.9** 0(0, 5) 268.6** Occasionally 0(0, 6) 0(0, 6) 0(0, 5) 0(0, 5) 0(0, 2) 0(0, 5) 0(0, 4) 0(0, 5) 0(0, 5) Frequently 0(0, 6) 0(0, 6) 0(0, 6) 0(0, 6) 0(0, 4) 0(0, 5) 0(0, 5) 0(0, 5) 0(0, 6) Sporting No 0(0, 7) 26.6** 0(0, 6) 39.8** 0(0, 6) 56.7** 0(0, 6) 128.5** 0(0, 3) 10.9** 0(0, 5) 84.4** 0(0, 5) 41.5** 0(0, 5) 28.4** 0(0, 6) 72.0** Occasionally 0(0, 6) 0(0, 6) 0(0, 5) 0(0, 6) 0(0, 2) 0(0, 5) 0(0, 5) 0(0, 5) 0(0, 5) Frequently 0(0, 6) 0(0, 6) 0(0, 5) 0(0, 6) 0(0, 1) 0(0, 5) 0(0, 4) 0(0, 5) 0(0, 5) Abbreviations: WMSDs=work-related musculoskeletal disorders; BMI=body mass index.
* P<0.05.
** P<0.01.Table 3. Analysis of pain scores of WMSDs with different demographic characteristics in China, 2018–2020.
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The epidemiological characteristics of WMSDs in key industries in China from January 2018 to June 2020 were investigated in this study. On the basis of data published last year (4), this paper continues to expand the sample size, reaching data of nearly 60,000 people, which is the largest population survey on WMSDs in China so far. The results of this study showed that the prevalence rate of WMSDs in any body part was 41.2%, and the most common parts were neck, shoulders, and lower back. The risk of WMSDs among female workers was 1.5 times that of male workers. With increases in age, the prevalence rate of WMSDs increased gradually and then decreased. A study on the burden of 354 diseases in 195 countries and regions demonstrated that from 1990 to 2017, lower back pain was the first disease leading to years lived with disability (YLD), and the prevalence rate of musculoskeletal disorders, lower back pain, and neck pain was 38.4% (36.4% to 40.2%), 30.0% (27.9% to 31.9%), and 44.4% (41.9% to 47.0%), respectively (5). According to the data, in 2017, the spot prevalence rate of neck pain in women was higher than that in men, although the results were not significant at P=0.05. It was also found that the prevalence rate of pain in the neck increased up to age 70–74 years and then decreased (6), which was similar to the results obtained from this study.
The results showed that biopharmaceutical manufacturing, vegetable greenhouses, medical personnel, civil aviation flight attendants, toy manufacturing, automobile manufacturing, and shipbuilding and related equipment manufacturing were industries or occupational groups with high prevalence rate of WMSDs exceeding 40%. Differences in the occurrence position of WMSDs depended on features of occupational activities. WMSDs of shipbuilding and related equipment manufacturing industry, construction industry, coal mining and cleaning industry, civil aviation flight attendants, automobile 4S shops, automobile manufacturing industry, petrochemical industry, and medical personnel were mainly concentrated in the neck, shoulders, and lower back. WMSDs in electronic equipment manufacturing and biopharmaceutical manufacturing occurred mainly in the upper back, and WMSDs in the furniture manufacturing industry occurred mainly in the ankles. However, in toy manufacturing, animal husbandry, and footwear industry, WMSDs not only occurred in the neck and shoulders but also the wrist. WMSDs occurred in the knees of vegetable greenhouse workers except for the lower back and neck. The disparity in results may be related to differences in affected parts, labor intensity, working conditions, and working methods. The prevalence rate of WMSDs in vegetable greenhouse workers was very high, which exceeded that of most workers in industrial and mining enterprises.
The pain scores in many parts of the female population were higher than those of the male population, which might be related to the fact that women were more sensitive to pain than men and were more willing to report pain (7). This study also found that the pain scores of those with BMI above 25, those who smoke, and those without physical exercise were higher than those of the corresponding low-dose groups. A prospective population study investigated the relationship between chronic pain and lifestyle factors and a correlation was found between pain and lifestyle such as smoking and infrequent physical exercise (8).
The study was subject to some limitations. First, research objects came from workers of 15 industries in China and some key industries related to WMSDs were not investigated, so the generalizability of the results was limited. Second, because of the nature of cross-sectional studies, making causal inference between risk factors and WMSDs was impossible. Finally, because the questionnaire survey was used in this study and the time period of the questionnaire survey was limited to past year, the resulting reporting bias and recall bias could influence the results.
In conclusion, the prevalence rate of WMSDs in key industries or occupations in China was relatively high. The most affected body parts were in the neck, shoulders, and lower back, and the results showed increases with increasing age and length of service. Women were more likely to suffer from WMSDs than men. The top three industries or occupational groups with the highest prevalence of WMSDs were pharmaceutical manufacturing, vegetable greenhouses, and medical staff. As a result, it is necessary to strengthen the publicity and education of ergonomics knowledge and improve the awareness of the occupational population on the basis of this study of WMSDs to promote effective intervention and control measures among the occupational population in order to reduce the impact of WMSDs. WMSDs in key industries should also be considered to be included in China's list of statutory occupational diseases.
Acknowledgments: All the participants involved in this study from Chongqing, Shanghai, Jiangsu, Zhejiang, Tianjin, Beijing, Hubei, Ningxia Hui Autonomous Region, Sichuan and Shaanxi Provincial Centers for Disease Prevention and Control, Hubei Provincial Hospital of Integrated Chinese & Western Medicine, Guangzhou Twelfth People’s Hospital Affiliated to Guangzhou Medical University, Liaoning Provincial Health Service Center, Guizhou Province Occupational Disease Prevention and Control Hospital, Shandong Academy of Occupational Health and Occupational Medicine, Civil Aviation Medical Center of China Civil Aviation Administration, Tianjin Occupational Disease Prevention and Control Hospital, Fujian Province Occupational Disease and Chemical Poisoning Prevention and Control Center, Guangdong Province Hospital for Occupational Disease Prevention and Treatment, and the Institute of Occupational Medicine of Jiangxi.
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