Utilization of Traditional Chinese Medicine Practitioners in Later Life in Mainland China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data
2.2. Covariates
2.2.1. Demographics
2.2.2. Health and Health Behaviors
2.2.3. Definition of TCM Use
2.3. Statistical Analysis
3. Results
3.1. Descriptive Statistics
3.2. Multivariate Analysis
3.3. Robustness Check
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
2012 | 2013 | 2014 | 2015 | 2016 | 2017 | |
---|---|---|---|---|---|---|
Visits to Chinese traditional medicines (TCM) practitioners (1,000,000) | 1945 | 2110 | 2280 | 2367 | 2501 | 2642 |
Total visits to practitioners (1,000,000) | 6888 | 7314 | 7602 | 7693 | 7932 | 8183 |
Proportion of TCM practitioners (%) | 28.2% | 28.9% | 30% | 30.8% | 31.5% | 32.3% |
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Characteristics | Proportion by Characteristics % (N) | Prevalence of TCM Users % | ||
---|---|---|---|---|
TCM Practitioner Utilization (n = 559) | non-TCM Practitioner Utilization (n = 5422) | |||
Overall | 14 | |||
Sex | ||||
Male (Ref) | 258 | 2393 | 13.9 | |
Female | 301 | 3029 | 14 | |
Age group | ||||
50–64 (Ref) | 321 | 3136 | 14.4 | |
65+ | 238 | 2286 | 13.2 | |
Marital Status | ||||
Never married | 13 | 42 | 31.3 | ** |
Currently married/cohabiting (Ref) | 465 | 4454 | 14 | |
Separated/divorced | 4 | 103 | 8 | |
Widowed | 77 | 822 | 12.9 | |
Income quintile | ||||
1 (poorest) | 112 | 919 | 15.3 | *** |
2 | 120 | 966 | 16.3 | *** |
3 | 129 | 1041 | 17.6 | *** |
4 | 142 | 1204 | 16.9 | *** |
5 (wealthiest) (Ref) | 48 | 1271 | 4 | |
Education | ||||
Primary or less | 258 | 1953 | 17 | *** |
Secondary | 112 | 1842 | 9.3 | * |
Tertiary or more (Ref) | 7 | 298 | 2.4 | |
Locality | ||||
Urban (Ref) | 83 | 2769 | 2.6 | |
Rural | 476 | 2653 | 22.9 | *** |
Province | ||||
Guangdong (Ref) | 28 | 775 | 3.3 | |
Hubei | 170 | 547 | 33.6 | *** |
Jilin | 5 | 318 | 1.6 | |
Shaanxi | 45 | 872 | 3.8 | |
Shandong | 242 | 876 | 25.4 | *** |
Shanghai | 41 | 931 | 5 | |
Yunnan | 14 | 497 | 2.7 | |
Zhejiang | 14 | 606 | 2.1 | |
Health Risk Behaviors | ` | |||
Tobacco | ||||
Used tobacco | 218 | 1754 | 15.7 | * |
Never used tobacco (Ref) | 340 | 3668 | 12.9 | |
Alcohol | ||||
Used alcohol | 197 | 1709 | 14.8 | |
Never used alcohol (Ref) | 361 | 3706 | 13.5 | |
Disease Diagnosis | ||||
Angina | ||||
Yes | 37 | 558 | 9.8 | * |
No (Ref) | 521 | 4851 | 14.4 | |
Asthma | ||||
Yes | 10 | 164 | 8.2 | |
No (Ref) | 549 | 5232 | 14.2 | |
Arthritis | ||||
Yes | 140 | 1491 | 12 | * |
No (Ref) | 419 | 3930 | 14.7 | |
Cataracts | ||||
Yes | 31 | 619 | 6.2 | *** |
No (Ref) | 523 | 4721 | 14.9 | |
Chronic lung disease | ||||
Yes | 68 | 588 | 14.6 | |
No (Ref) | 490 | 4830 | 13.9 | |
Depression | ||||
Yes | 2 | 556 | 16.3 | |
No (Ref) | 21 | 5394 | 13.9 | |
Diabetes | ||||
Yes | 23 | 495 | 7.6 | ** |
No (Ref) | 535 | 4918 | 14.6 | |
Hypertension | ||||
Yes | 193 | 1793 | 11.7 | * |
No (Ref) | 383 | 3588 | 14.9 | |
Stroke | ||||
Yes | 21 | 254 | 11.6 | |
No (Ref) | 538 | 5166 | 14.1 |
Multivariate Logistic Regression: Adjusted Odds Ratios (OR) | |||||||||
---|---|---|---|---|---|---|---|---|---|
Model 1 | Model 2A | Model 2B | |||||||
OR | p-value | OR | p-value | OR | p-value | CI | |||
Sex | |||||||||
Male (Ref) | |||||||||
Female | 0.98 | 0.883 | 1.49 | 0.030 | 1.32 | 0.194 | 0.87–2.01 | ||
Age group | |||||||||
50–64 (Ref) | |||||||||
65+ | 1.20 | 0.243 | 1.49 | 0.006 | 1.33 | 0.079 | 1.33–1.84 | ||
Marital Status | |||||||||
Never married | 0.87 | 0.857 | 2.32 | 0.173 | 1.09 | 0.908 | 0.26–4.51 | ||
Currently married/cohabiting (Ref) | |||||||||
Separated/divorced | 0.69 | 0.571 | 0.63 | 0.455 | 0.61 | 0.435 | 0.18–2.10 | ||
Widowed | 0.95 | 0.858 | 0.84 | 0.498 | 0.84 | 0.514 | 0.49–1.43 | ||
Income quintile | |||||||||
1 (poorest) | 1.08 | 0.817 | 0.94 | 0.833 | 1.07 | 0.836 | 0.57–2.02 | ||
2 | 0.99 | 0.983 | 1.17 | 0.524 | 0.95 | 0.871 | 0.54–1.69 | ||
3 | 1.38 | 0.222 | 2.05 | 0.002 | 1.34 | 0.263 | 0.80–2.24 | ||
4 | 1.61 | 0.043 | 2.31 | <0.001 | 1.58 | 0.053 | 0.99–2.50 | ||
5 (wealthiest) (Ref) | |||||||||
Education | |||||||||
Primary or less | 1.24 | 0.688 | 0.93 | 0.884 | 1.20 | 0.743 | 0.40–3.47 | ||
Secondary | 0.92 | 0.874 | 0.81 | 0.688 | 0.86 | 0.771 | 0.31–2.40 | ||
Tertiary or more (Ref) | |||||||||
Locality | |||||||||
Urban (Ref) | |||||||||
Rural | 13.54 | <0.001 | 13.30 | <0.001 | 12.96 | <0.001 | 8.24–20.4 | ||
Province | |||||||||
Guangdong (Ref) | |||||||||
Hubei | 6.67 | <0.001 | 7.17 | <0.001 | 3.82–13.4 | ||||
Jilin | 1.15 | 0.814 | 1.21 | 0.762 | 0.35–4.26 | ||||
Shaanxi | 0.26 | <0.001 | 0.27 | <0.001 | 0.13–0.56 | ||||
Shandong | 3.65 | <0.001 | 4.21 | <0.001 | 2.24–7.89 | ||||
Shanghai | 0.80 | 0.547 | 0.92 | 0.819 | 0.43–1.93 | ||||
Yunnan | 0.23 | 0.002 | 0.24 | 0.004 | 0.09–0.64 | ||||
Zhejiang | 0.16 | 0.001 | 0.16 | 0.001 | 0.05–0.49 | ||||
Health Risk Behaviors | |||||||||
Tobacco | |||||||||
Used tobacco | 0.82 | 0.275 | 0.80 | 0.276 | 0.53–1.20 | ||||
Never used tobacco (Ref) | |||||||||
Alcohol | |||||||||
Used alcohol | 1.01 | 0.935 | 0.93 | 0.678 | 0.65–1.32 | ||||
Never used alcohol (Ref) | |||||||||
Disease Diagnosis | |||||||||
Angina | |||||||||
Yes | 0.85 | 0.494 | 0.65 | 0.112 | 0.38–1.11 | ||||
No (Ref) | |||||||||
Asthma | |||||||||
Yes | 0.50 | 0.192 | 0.48 | 0.194 | 0.16–1.45 | ||||
No (Ref) | |||||||||
Arthritis | |||||||||
Yes | 0.91 | 0.516 | 0.88 | 0.429 | 0.64–1.21 | ||||
No (Ref) | |||||||||
Cataracts | |||||||||
Yes | 0.73 | 0.331 | 0.98 | 0.952 | 0.51–1.89 | ||||
No (Ref) | |||||||||
Chronic lung disease | |||||||||
Yes | 1.76 | 0.007 | 1.97 | 0.005 | 1.23–3.15 | ||||
No (Ref) | |||||||||
Depression | |||||||||
Yes | 2.38 | 0.423 | 3.38 | 0.133 | 0.69–16.5 | ||||
No (Ref) | |||||||||
Diabetes | |||||||||
Yes | 0.76 | 0.372 | 0.62 | 0.150 | 0.32–1.19 | ||||
No (Ref) | |||||||||
Hypertension | |||||||||
Yes | 0.97 | 0.856 | 0.86 | 0.366 | 0.62–1.19 | ||||
No (Ref) | |||||||||
Stroke | |||||||||
Yes | 1.01 | 0.972 | 0.95 | 0.892 | 0.47–1.94 | ||||
No (Ref) |
(1) Guangdong, Shanghai, and Zhejiang | (2) Hubei | (3) Shandong | (4) Jilin, Shaanxi, and Yunnan | |||||
---|---|---|---|---|---|---|---|---|
Urban | Rural | Urban | Rural | Urban | Rural | Urban | Rural | |
% Overall | 49.8 | 50.2 | 47.5 | 52.5 | 49.3 | 50.7 | 49.2 | 50.8 |
% of TCM Practitioner utilization | 1.5 | 5.7 | 5 | 57 | 1.3 | 39.5 | 5.6 | 2.6 |
Income quintile | ||||||||
% of quintile 1 | 4.5 | 31.6 | 15.6 | 34.8 | 0.3 | 5.1 | 25 | 28.6 |
% of quintile 2 | 8.7 | 20.3 | 19.2 | 30.7 | 0.6 | 19 | 21.9 | 32.3 |
% of quintile 3 | 18.4 | 14.4 | 23.2 | 15.6 | 9.1 | 34.2 | 27.1 | 19.8 |
% of quintile 4 | 25 | 15.6 | 26.5 | 14 | 29.6 | 36.7 | 18.7 | 13.4 |
% of quintile 5 | 43.4 | 18.1 | 15.4 | 4.9 | 60.3 | 5 | 7.3 | 5.9 |
Tobacco | ||||||||
% using tobacco | 26.1 | 38 | 37.6 | 46.4 | 17 | 41.2 | 31.1 | 36.3 |
Chronic lung disease | ||||||||
% diagnosed | 8.5 | 6.9 | 15.7 | 8.8 | 6.6 | 4.9 | 11 | 8.2 |
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Aw, J.Y.H.; Sbirakos Yiengprugsawan, V.; Gong, C.H. Utilization of Traditional Chinese Medicine Practitioners in Later Life in Mainland China. Geriatrics 2019, 4, 49. https://doi.org/10.3390/geriatrics4030049
Aw JYH, Sbirakos Yiengprugsawan V, Gong CH. Utilization of Traditional Chinese Medicine Practitioners in Later Life in Mainland China. Geriatrics. 2019; 4(3):49. https://doi.org/10.3390/geriatrics4030049
Chicago/Turabian StyleAw, Jessica Yi Han, Vasoontara Sbirakos Yiengprugsawan, and Cathy Honge Gong. 2019. "Utilization of Traditional Chinese Medicine Practitioners in Later Life in Mainland China" Geriatrics 4, no. 3: 49. https://doi.org/10.3390/geriatrics4030049
APA StyleAw, J. Y. H., Sbirakos Yiengprugsawan, V., & Gong, C. H. (2019). Utilization of Traditional Chinese Medicine Practitioners in Later Life in Mainland China. Geriatrics, 4(3), 49. https://doi.org/10.3390/geriatrics4030049