| Literature DB >> 31652897 |
Meng-Chuan Tsai1, Yu-Hsien Kuo2, Chih-Hsin Muo3, Li-Wei Chou4,5,6, Chung-Yen Lu7,8.
Abstract
Carpal tunnel syndrome (CTS) is a common musculoskeletal disorder and an occupational disease caused by repeated exercise or overuse of the hand. We investigated the characteristics of traditional Chinese medicine (TCM) use by practitioners in CTS patients, including demographic variables, socioeconomic status, previous medical conditions, health care use, and hospital characteristics for TCM health care. This cross-sectional study identified 25,965 patients newly diagnosed with CTS based on the first medical diagnosis recorded between 1999 and 2013 in the nationwide representative insurance database of Taiwan. The date of initial CTS diagnosis in outpatient data was defined as the index date, and four patients were excluded because of missing gender-related information. Patients who used TCM care as the first option at their diagnosis were classified as TCM users (n = 677; 2.61%), and all others were TCM non-users (n = 25,288; 97.4%). In the all variables-adjusted model, female patients had an adjusted odds ratio (OR; 95% CI) of TCM use of 1.35 (1.11-1.66). National Health Insurance (NHI) registration was associated with higher odds ratios of TCM use in central, southern, and eastern Taiwan than in northern Taiwan (ORs = 1.43, 1.86, and 1.82, respectively). NHI registration was associated with higher odds ratios of TCM use in rural cities than in urban cities (OR (95% CI) = 1.33 (1.02-1.72)). The TCM group had a 20% less likelihood of exhibiting symptoms, signs, and ill-defined conditions and injury and poisoning. The TCM group had a 56% lower likelihood of having diseases of the musculoskeletal system and connective tissue. Multi-level model outcomes were similar to the results of the all variables-adjusted model, except for the NHI registration outcome in rural and urban cities (OR [95% CI] = 1.33 [0.98-1.81]). Significant associations between the number of TCM visits and TCM use were observed in all logistic regression models. The study presented key demographic characteristics, health care use, and medical conditions associated with TCM use for CTS. Previous experience of TCM use may affect the use of TCM for CTS treatment. This information provides a reference for the allocations of relevant medical resources and health care providers.Entities:
Keywords: carpal tunnel syndrome; occupational disease; traditional Chinese medicine
Mesh:
Year: 2019 PMID: 31652897 PMCID: PMC6862695 DOI: 10.3390/ijerph16214086
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Flowchart of study sample selection.
Baseline characteristics of patients with and without TCM use as the preferred medical care for carpal tunnel syndrome at diagnosis.
| Characteristics | Total | Non-Users of TCM | TCM Users |
|
|---|---|---|---|---|
| Age at diagnosis, yr, | <0.0001 | |||
| <18 | 54 (0.21) | 52 (0.21) | 2 (0.30) | |
| 18–30 | 1644 (6.33) | 1580 (6.25) | 64 (9.45) | |
| 31–45 | 7689 (29.6) | 7424 (29.4) | 265 (39.1) | |
| 46–65 | 13,360 (51.5) | 13,058 (51.6) | 302 (44.6) | |
| >65 | 3218 (12.4) | 3174 (12.6) | 44 (6.50) | |
| Mean(SD) | 50.4 (12.9) | 50.5 (1.29) | 46.3 (12.2) | <0.0001 |
| Female, | 18,505 (71.3) | 17,972 (71.1) | 533 (78.7) | <0.0001 |
| Geographic region of registration units for NHI, | <0.0001 | |||
| Northern | 11,793 (45.4) | 11,573 (45.8) | 220 (32.5) | |
| Central | 5148 (19.8) | 4998 (19.8) | 150 (22.2) | |
| Southern | 7692 (29.6) | 7425 (29.4) | 267 (39.4) | |
| Eastern | 1332 (5.12) | 1292 (5.11) | 40 (5.91) | |
| Urbanization level of registration units for NHI *, | 0.01 | |||
| Urban | 15,856 (61.1) | 15,459 (61.1) | 397 (58.6) | |
| Satellite | 7743 (29.8) | 7547 (29.8) | 196 (29.0) | |
| Rural | 2366 (9.11) | 2282 (9.02) | 84 (12.4) | |
| Previous medical conditions †, | ||||
| Month income (NTD), | 0.02 | |||
| <15,840 | 8429 (32.5) | 8176 (32.3) | 253 (37.4) | |
| 15,840–25,000 | 11,656 (44.9) | 11,369 (45.0) | 287 (42.4) | |
| >25,000 | 5880 (22.7) | 5743 (22.7) | 137 (20.2) | |
| Occupation, | 0.99 | |||
| White collar | 13,099 (50.5) | 12,758 (50.5) | 341 (50.4) | |
| Blue collar | 11,022 (42.5) | 10,734 (42.5) | 288 (42.5) | |
| Others | 1844 (7.10) | 1796 (7.10) | 48 (7.09) | |
| Infectious and parasitic diseases | 3449 (13.3) | 3366 (13.3) | 83 (12.3) | 0.43 |
| Neoplasms | 2067 (7.96) | 2030 (8.03) | 37 (5.47) | 0.02 |
| Endocrine, nutritional, blood and metabolic diseases, and immunity disorders | 6504 (25.1) | 6386 (25.3) | 118 (17.4) | <0.0001 |
| Mental disorders, diseases of the nervous system and sense organs | 16,042 (61.8) | 15,667 (62.0) | 375 (55.4) | 0.0005 |
| Diseases of the circulatory system | 7852 (30.2) | 7711 (30.5) | 141 (20.8) | <0.0001 |
| Diseases of the respiratory system | 17,108 (65.9) | 17,108 (67.7) | 457 (67.5) | 0.93 |
| Diseases of the digestive system | 15,854 (61.1) | 15,444 (61.1) | 410 (60.6) | 0.79 |
| Diseases of the genitourinary system | 8745 (33.7) | 8520 (33.7) | 225 (33.2) | 0.80 |
| Diseases of the skin and subcutaneous tissue | 6780 (26.1) | 6625 (26.2) | 155 (22.9) | 0.054 |
| Diseases of the musculoskeletal system and connective tissue | 17,174 (66.1) | 16,838 (66.6) | 336 (49.6) | <0.0001 |
| Symptoms, signs, and ill-defined conditions | 11,786 (45.4) | 11,493 (45.5) | 293 (43.3) | 0.26 |
| Injury and poisoning | 8435 (32.5) | 8230 (32.6) | 205 (30.3) | 0.21 |
| Supplementary classification | 4456 (17.2) | 4348 (17.2) | 108 (16.0) | 0.40 |
| Others | 215 (0.83) | 210 (0.83) | 5 (0.74) | 0.79 |
| Health care utilization †, | ||||
| Number of outpatient visit | <0.0001 | |||
| Q1 (25%) | 13 | 13 | 12 | |
| Q2 (50%) | 23 | 23 | 20 | |
| Q3 (75%) | 37 | 37 | 33 | |
| Median (interquartile range) | 23 (24) | 23 (24) | 20 (21) | |
| Number of inpatient visit | 0.009 | |||
| Q1 (25%) | 0 | 0 | 0 | |
| Q2 (50%) | 0 | 0 | 0 | |
| Q3 (75%) | 0 | 0 | 0 | |
| Median (interquartile range) | 0 (0) | 0 (0) | 0 (0) | |
| Number of TCM visit | <0.0001 | |||
| Q1 (25%) | 0 | 0 | 2 | |
| Q2 (50%) | 0 | 0 | 4 | |
| Q3 (75%) | 3 | 3 | 8 | |
| Median (interquartile range) | 0 (3) | 0 (3) | 4 (6) |
Abbreviations: TCM, traditional Chinese medicine. Values are number of patients and percentages unless otherwise indicated. * Directorate-General Budget, Accounting and Statistics; National statistics of regional standard classification data; Taipei: Accounting and Statistics; 1993. † Defined by searching claims data within one year before index date. Comorbidities were considered to be present if the diagnosis codes were recorded on at least one inpatient claim or two outpatient claims. n, number of patients with carpal tunnel syndrome.
Characteristics of hospitals where patients received medical care after their diagnosis of carpal tunnel syndrome.
| Characteristics | Total | Non-Users of TCM | TCM Users |
|
|---|---|---|---|---|
| Locations of hospital where subjects received the diagnosis, | <0.0001 | |||
| Northern | 11,517 (44.4) | 11,319 (44.8) | 198 (29.3) | |
| Central | 5337 (20.6) | 5184 (20.5) | 153 (22.6) | |
| Southern | 7849 (30.2) | 7568 (29.9) | 281 (41.5) | |
| Eastern | 1262 (4.9) | 1217 (4.8) | 45 (6.7) | |
| Accreditation level of hospital where subjects received the diagnosis, | <0.0001 | |||
| Medical center | 5097 (19.6) | 5067 (20.0) | 30 (4.4) | |
| District hospital | 8367 (32.2) | 8314 (32.9) | 53 (7.8) | |
| Local hospital | 5707 (22.0) | 5681 (22.5) | 26 (3.8) | |
| Clinics and others | 6794 (26.2) | 6226 (24.6) | 568 (83.9) |
Demographic characteristics, health care use, and medical conditions within a year before diagnosis were associated with using TCM as the preferred medical care in patients with carpal tunnel syndrome.
| Characteristics | Odds Ratio (95% Confidence Interval) † | ||||
|---|---|---|---|---|---|
| Crude Model | Age and Sex Adjusted Model | Selected Variables Adjusted Model * | All Variables Adjusted Model | Multilevel Model | |
| Age at diagnosis, year (vs. ≤30) | |||||
| 31–45 | 0.90 (0.68–1.21) | - | 1.08 (0.79–1.47) | 1.07 (0.78–1.47) | 1.05 (0.76–1.44) |
| 46–65 | 0.58 (0.44–0.78) | - | 0.90 (0.65–1.24) | 0.87 (0.63–1.22) | 0.86 (0.62–1.20) |
| >65 | 0.35 (0.23–0.52) | - | 0.78 (0.51–1.22) | 0.73 (0.47–1.15) | 0.73 (0.46–1.15) |
| Female (vs. Male) | 1.51 (1.25–1.82) | - | 1.33 (1.10–1.62) | 1.35 (1.11–1.66) | 1.36 (1.11–1.66) |
| Geographic region of registration units for NHI (vs. northern) | |||||
| Central | 1.58 (1.28–1.95) | 1.56 (1.26–1.92) | 1.41 (1.12–1.77) | 1.43 (1.13–1.79) | 1.36 (1.01–1.82) |
| Southern | 1.89 (1.58–2.27) | 1.90 (1.58–2.27) | 1.86 (1.54–2.26) | 1.86 (1.53–2.26) | 1.91 (1.47–2.48) |
| Eastern | 1.63 (1.16–2.29) | 1.64 (1.16–2.30) | 1.85 (1.29–2.65) | 1.82 (1.26–2.61) | 1.84 (1.19–2.84) |
| Urbanization level of registration units for NHI * (vs. urban) | |||||
| Satellite | 1.01 (0.85–1.20) | 1.01 (0.85–1.20) | 0.89 (0.74–1.07) | 0.90 (0.75–1.08) | 0.93 (0.74–1.17) |
| Rural | 1.43 (1.13–1.82) | 1.47 (1.15–1.86) | 1.32 (1.02–1.71) | 1.33 (1.02–1.72) | 1.33 (0.98–1.81) |
| Month income (vs. >25,000) | |||||
| <15,840 | 1.30 (1.05–1.60) | 1.09 (0.88–1.36) | 1.09 (0.87–1.37) | 1.09 (0.86–1.39) | 1.12 (0.88–1.43) |
| 15,840–25,000 | 1.06 (0.86–1.30) | 1.03 (0.84–1.27) | 0.98 (0.79–1.21) | 0.98 (0.77–1.23) | 1.00 (0.79–1.27) |
| Occupation (vs. white collar) | |||||
| Blue collar | 1.00 (0.86–1.18) | 1.05 (0.89–1.23) | - | 1.02 (0.84–1.24) | 0.99 (0.81–1.22) |
| Others | 1.00 (0.74–1.36) | 1.11 (0.81–1.50) | - | 1.06 (0.76–1.47) | 1.09 (0.85–1.39) |
| Common conditions of pediatric patients in outpatient settings †, (yes vs. no) | |||||
| Infectious and parasitic diseases | 0.91 (0.72–1.15) | 0.95 (0.75–1.20) | - | 1.08 (0.84–1.38) | 1.09 (0.85–1.39) |
| Neoplasms | 0.66 (0.47–0.93) | 0.68 (0.48–0.95) | 0.76 (0.54–1.07) | 0.76 (0.54–1.08) | 0.76 (0.54–1.08) |
| Endocrine, nutritional, blood and metabolic diseases, and immunity disorders | 0.63 (0.51–0.76) | 0.77 (0.62–0.94) | 0.91 (0.73–1.13) | 0.90 (0.72–1.12) | 0.91 (0.73–1.13) |
| Mental disorders, diseases of the nervous system and sense organs | 0.76 (0.65–0.89) | 0.83 (0.71–0.97) | 0.86 (0.72–1.01) | 0.86 (0.72–1.01) | 0.85 (0.72–1.01) |
| Diseases of the circulatory system | 0.60 (0.50–0.72) | 0.80 (0.65–0.97) | 0.95 (0.76–1.18) | 0.95 (0.76–1.18) | 0.93 (0.75–1.16) |
| Diseases of the respiratory system | 0.99 (0.84–1.17) | 0.95 (0.81–1.12) | - | 0.99 (0.83–1.19) | 1.00 (0.83–1.19) |
| Diseases of the digestive system | 0.98 (0.84–1.14) | 1.03 (0.88–1.21) | - | 1.11 (0.93–1.31) | 1.09 (0.92–1.30) |
| Diseases of the genitourinary system | 0.98 (0.83–1.15) | 0.88 (0.74–1.04) | - | 0.91 (0.76–1.10) | 0.91 (0.76–1.10) |
| Diseases of the skin and subcutaneous tissue | 0.84 (0.70–1.00) | 0.83 (0.69–0.99) | - | 0.87 (0.72–1.06) | 0.87 (0.72–1.06) |
| Diseases of the musculoskeletal system and connective tissue | 0.49 (0.42–0.58) | 0.55 (0.47–0.64) | 0.44 (0.37–0.52) | 0.44 (0.37–0.52) | 0.44 (0.37–0.53) |
| Symptoms, signs, and ill-defined conditions | 0.92 (0.79–1.07) | 0.96 (0.82–1.12) | - | 0.81 (0.68–0.96) | 0.81 (0.68–0.97) |
| Injury and poisoning | 0.90 (0.76–1.06) | 0.92 (0.78–1.09) | - | 0.79 (0.66–0.95) | 0.80 (0.64–0.95) |
| Supplementary classification | 0.91 (0.74–1.13) | 1.01 (0.82–1.25) | - | 1.13 (0.90–1.42) | 1.12 (0.89–1.41) |
| Others | 0.89 (0.37–2.16) | 0.95 (0.39–2.31) | - | 0.93 (0.37–2.30) | 0.93 (0.37–2.32) |
| Health care utilization † | |||||
| Number of outpatient visit (vs. <Q1) | |||||
| Q1–Q2 | 0.96 (0.79–1.18) | 0.98 (0.80–1.21) | 0.80 (0.64–1.00) | 0.84 (0.66–1.07) | 0.85 (0.67–1.08) |
| Q2–Q3 | 0.79 (0.64–0.97) | 0.84 (0.68–1.05) | 0.62 (0.48–0.79) | 0.68 (0.51–0.91) | 0.69 (0.52–0.93) |
| ≥Q3 | 0.63 (0.50–0.79) | 0.78 (0.62–0.99) | 0.53 (0.39–0.71) | 0.62 (0.43–0.89) | 0.62 (0.43–0.89) |
| Number of inpatient visit (vs. no) | 0.72 (0.55–0.93) | 0.79 (0.60–1.02) | 0.95 (0.72–1.25) | 0.97 (0.73–1.28) | 0.97 (0.73–1.28) |
| Number of TCM visit (vs. <Q3) | 3.82 (3.27–4.47) | 3.67 (3.14–4.29) | 5.41 (4.54–6.46) | 5.80 (4.84–6.96) | 5.79 (4.83–6.95) |
Abbreviations: TCM, traditional Chinese medicine. * Model was adjusted for variables statistically significantly associated with TCM use in the univariate analysis. † Logistic regression model.