Assessing Health-Related Quality of Life of Chinese Adults in Heilongjiang Using EQ-5D-3L
Abstract
:1. Introduction
2. Methods
2.1. Study Design and Data Collection
2.2. Instruments
2.3. Data Analysis
3. Results
3.1. Characteristics of Respondents
3.2. Bivariate Analyses
3.3. Multivariate Analyses
4. Discussion
5. Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Brauer, C.A.; Rosen, A.B.; Greenberg, D.; Neumann, P.J. Trends in the Measurement of Health Utilities in Published Cost-Utility Analyses. Value Health 2006, 9, 213–218. [Google Scholar] [CrossRef] [PubMed]
- Greenberg, D.; Earle, C.; Fang, C.-H.; Eldar-Lissai, A.; Neumann, P.J. When is cancer care cost-effective? A systematic overview of cost–utility analyses in oncology. J. Natl. Cancer Inst. 2010, 102, 82–88. [Google Scholar] [CrossRef] [PubMed]
- Marra, C.A.; Woolcott, J.C.; Kopec, J.A.; Shojania, K.; Offer, R.; Brazier, J.E.; Esdaile, J.M.; Anis, A.H. A comparison of generic, indirect utility measures (the HUI2, HUI3, SF-6D, and the EQ-5D) and disease-specific instruments (the RAQoL and the HAQ) in rheumatoid arthritis. Soc. Sci. Med. 2005, 60, 1571–1582. [Google Scholar] [CrossRef] [PubMed]
- Drummond, M.F.; Sculpher, M.J.; Torrance, G.W.; O’Brien, B.J.; Stoddart, G.L. Methods for the Economic Evaluation of Health Care Programme, 3rd ed.; Oxford Medical Publications: New York, NY, USA, 2005. [Google Scholar]
- Burstrom, K.; Johannesson, M.; Diderichsen, F. A comparison of individual and social time trade-off values for health states in the general population. Health Policy 2006, 76, 359–370. [Google Scholar] [CrossRef] [PubMed]
- Burstrom, K.; Sun, S.; Gerdtham, U.G.; Henriksson, M.; Johannesson, M.; Levin, L.A.; Zethraeus, N. Swedish experience-based value sets for EQ-5D health states. Qual. Life Res. 2014, 23, 431–442. [Google Scholar] [CrossRef] [PubMed]
- Mctaggart-Cowan, H.; Teckle, P.; Peacock, S. Mapping utilities from cancer-specific health-related quality of life instruments: A review of the literature. Expert Rev. Pharm. Outcomes Res. 2013, 13, 753–765. [Google Scholar] [CrossRef] [PubMed]
- Brooks, R. EuroQol: The current state of play. Health Policy 1996, 37, 53–72. [Google Scholar] [CrossRef]
- Dolan, P. Modeling valuations for EuroQol health states. Med. Care 1997, 35, 1095–1108. [Google Scholar] [CrossRef] [PubMed]
- Feeny, D.; Furlong, W.; Boyle, M.; Torrance, G.W. Multi-attribute health status classification systems. Health Utilities Index. Pharmacoeconomics 1995, 7, 490–502. [Google Scholar] [CrossRef] [PubMed]
- Torrance, G.W.; Feeny, D.H.; Furlong, W.J.; Barr, R.D.; Zhang, Y.; Wang, Q. Multiattribute utility function for a comprehensive health status classification system. Health Utilities Index Mark 2. Med. Care 1996, 34, 702–722. [Google Scholar] [CrossRef] [PubMed]
- Kharroubi, S.A.; Brazier, J.E.; Roberts, J.; O’Hagan, A. Modelling SF-6D health state preference data using a nonparametric Bayesian method. J. Health Econ. 2007, 26, 597–612. [Google Scholar] [CrossRef] [PubMed]
- Brazier, J.; Roberts, J.; Deverill, M. The estimation of a preference-based measure of health from the SF-36. J. Health Econ. 2002, 21, 271–292. [Google Scholar] [CrossRef]
- Brazier, J.; Usherwood, T.; Harper, R.; Thomas, K. Deriving a preference-based single index from the UK SF-36 Health Survey. J. Clin. Epidemiol. 1998, 51, 1115–1128. [Google Scholar] [CrossRef]
- Patrick, D.L. Measuring health-related quality of life. Ann. Intern. Med. 1993, 118, 622–629. [Google Scholar]
- Kopec, J.A.; Willison, K.D. A comparative review of four preference-weighted measures of health-related quality of life. J. Clin. Epidemiol. 2003, 56, 317–325. [Google Scholar] [CrossRef]
- Räsänen, P.; Roine, E.; Sintonen, H.; Semberg-Konttinen, V.; Ryynänen, O.P.; Roine, R. Use of quality-adjusted life years for the estimation of effectiveness of health care: A systematic literature review. Int. J. Technol. Assess. Health Care 2006, 22, 235–241. [Google Scholar] [CrossRef] [PubMed]
- Oppe, M.; Devlin, N.J.; SZENDE, A. EQ-5D Value Sets: Inventory, Comparative Review and User Guide; Springer: Berlin, Germany, 2007. [Google Scholar]
- Chang, T.J.; Tarn, Y.H.; Hsieh, C.L.; Liou, W.S.; Shaw, J.W.; Chiou, X.G. Taiwanese version of the EQ-5D: Validation in a representative sample of the Taiwanese population. J. Formos. Med. Assoc. 2007, 106, 1023–1031. [Google Scholar] [CrossRef]
- Luo, N.; Chew, L.H.; Fong, K.Y.; Koh, D.R.; Ng, S.C.; Yoon, K.H.; Vasoo, S.; Li, S.C.; Thumboo, J. Validity and reliability of the EQ-5D self-report questionnaire in Chinese-speaking patients with rheumatic diseases in Singapore. Ann. Acad. Med. Singap. 2003, 32, 685–690. [Google Scholar] [PubMed]
- Wang, H.; Kindig, D.A.; Mullahy, J. Variation in Chinese population health related quality of life: Results from a EuroQol study in Beijing, China. Qual. Life Res. 2005, 14, 119–132. [Google Scholar] [CrossRef] [PubMed]
- Liu, G.G.; Hu, S.L.; Wu, J.H. China guidelines for pharmacoeconomic evaluations (2011). China J. Pharm. Econ. 2011, 3, 8–50. [Google Scholar]
- Liu, G.G.; Wu, H.; Li, M.; Gao, C.; Luo, N. Chinese Time Trade-Off Values for EQ-5D Health States. Value Health 2014, 17, 597–604. [Google Scholar] [CrossRef] [PubMed]
- Sun, S.; Chen, J.; Johannesson, M.; Kind, P.; Xu, L.; Zhang, Y.; Burström, K. Population health status in China: EQ-5D results, by age, sex and socio-economic status, from the National Health Services Survey 2008. Qual. Life Res. 2010, 20, 309–320. [Google Scholar] [CrossRef] [PubMed]
- Ma, L.; Chen, J.; Gu, X.; Zhao, F.; Gao, X.; Wu, R.; Liu, Z.; Ning, Y.; Cao, S. Health related quality of life based on EQ-5D in cervical carcinorma patients. Matern. Child Health Care Chin. 2013, 21, 3471–3473. [Google Scholar]
- Ji, K.; Zhou, W.; Chen, J.-Y. Evaluation of health-related quality of life of married women in childbearing age in rural China. Acta Univ. Med. NANJING (Soc. Sci.) 2011, 3, 181–185. [Google Scholar]
- He, M.; Wu, M. A preliminary analysis of the relationship between the living mode and the health status of the elderly in a city in Beijing City: A health measurement scale based on EQ-5D. Chin. J. Gerontol. 2009, 4, 478–481. [Google Scholar]
- Han, Y.; Wu, J.; Cong, H.; ZHou, J.; Xu, C. Validity and Sensitivity of the SF-6D and EQ-5D in Chinese Patients with Stable Angina Pectoris. Chin. J. Health Stat. 2013, 6, 829–832. [Google Scholar]
- Norman, R.; Church, J.; van den Berg, B.; Goodall, S. Australian health-related quality of life population norms derived from the SF-6D. Aust. N. Z. J. Public Health 2013, 37, 17–23. [Google Scholar] [CrossRef] [PubMed]
- Gundgaard, J.; Lauridsen, J. A decomposition of income-related health inequality applied to EQ-5D. Eur. J. Health Econ. 2006, 7, 231–237. [Google Scholar] [CrossRef] [PubMed]
- Luo, N. Self-Reported Health Status of the General Adult U.S. Population as Assessed by the EQ-5D and Health Utilities Index. Med. Care 2005, 43, 1078. [Google Scholar] [CrossRef] [PubMed]
- Perneger, T.V.; Combescure, C.; Courvoisier, D.S. General Population Reference Values for the French Version of the EuroQol EQ-5D Health Utility Instrument. Value Health 2010, 13, 631–635. [Google Scholar] [CrossRef] [PubMed]
- Sorensen, J.; Davidsen, M.; Gudex, C.; Pedersen, K.M.; Bronnum-Hansen, H. Danish EQ-5D population norms. Scand. J. Public Health 2009, 37, 467–474. [Google Scholar] [CrossRef] [PubMed]
- Golicki, D. General population reference values for 3-level EQ-5D (EQ-5D-3L) questionnaire in Poland. Pol. Arch. Med. Wewn. 2015, 125, 18–26. [Google Scholar] [PubMed]
- Clemens, S.; Begum, N.; Harper, C.; Whitty, J.A.; Scuffham, P.A. A comparison of EQ-5D-3L population norms in Queensland, Australia, estimated using utility value sets from Australia, the UK and USA. Qual. Life Res. 2014, 23, 2375–2381. [Google Scholar] [CrossRef] [PubMed]
- Yu, S.-T.; Chang, H.-Y.; Yao, K.-P.; Lin, Y.-H.; Hurng, B.-S. Validity of EQ-5D in general population of Taiwan: Results of the 2009 National Health Interview and Drug Abuse Survey of Taiwan. Qual. Life Res. 2015, 24, 2541–2548. [Google Scholar] [CrossRef] [PubMed]
- Abdin, E.; Subramaniam, M.; Vaingankar, J.A.; Luo, N.; Chong, S.A. Measuring health-related quality of life among adults in Singapore: Population norms for the EQ-5D. Qual. Life Res. 2013, 22, 2983–2991. [Google Scholar] [CrossRef] [PubMed]
- Abdin, E.; Subramaniam, M.; Vaingankar, J.A.; Luo, N.; Chong, S.A. Population norms for the EQ-5D index scores using Singapore preference weights. Qual. Life Res. 2014, 24, 1545–1553. [Google Scholar] [CrossRef] [PubMed]
- Bammann, K.; Kularatna, S.; Whitty, J.A.; Johnson, N.W.; Jayasinghe, R.; Scuffham, P.A. EQ-5D-3L Derived Population Norms for Health Related Quality of Life in Sri Lanka. PLoS ONE 2014, 9, e108434. [Google Scholar]
- Shiroiwa, T.; Fukuda, T.; Ikeda, S.; Igarashi, A.; Noto, S.; Saito, S.; Shimozuma, K. Japanese population norms for preference-based measures: EQ-5D-3L, EQ-5D-5L, and SF-6D. Qual. Life Res. 2015, 25, 707–719. [Google Scholar] [CrossRef] [PubMed]
- Fujikawa, A.; Suzue, T.; Jitsunari, F.; Hirao, T. Evaluation of health-related quality of life using EQ-5D in Takamatsu, Japan. Environ. Health Prev. Med. 2010, 16, 25–35. [Google Scholar] [CrossRef] [PubMed]
- Centre for Health Statistics and Information of Ministry of Health of People’s Republic of China. An Analysis Report National Health Services Survey in China, 2008; Peking Union Medical College Press: Beijing, China, 2009.
- Group, E. EuroQol—A new facility for the measurement of health-related quality of life. Health Policy 1990, 16, 199–208. [Google Scholar]
- Rabin, R.; De-Charro, F. EQ-5D: A measure of health status from the EuroQol Group. Ann. Med. 2001, 33, 337–343. [Google Scholar] [CrossRef] [PubMed]
- Dolan, P.; Kahneman, D. Interpretations of Utility and Their Implications for the Valuation of Health. Econ. J. 2008, 118, 215–234. [Google Scholar] [CrossRef]
- Liu, G.G. China Guidelines for Pharmacoeconomic Evaluations and Manual; Beijing Science Press: Beijing, China, 2015. [Google Scholar]
- Kivits, J.; Erpelding, M.L.; Guillemin, F. Social determinants of health-related quality of life. Rev. Dépidémiol. Santé Publ. 2013, 61, S189–S194. [Google Scholar] [CrossRef] [PubMed]
- Torrance, N.; Lawson, K.D.; Afolabi, E.; Bennett, M.I.; Serpell, M.G.; Dunn, K.M.; Smith, B.H. Estimating the burden of disease in chronic pain with and without neuropathic characteristics: Does the choice between the EQ-5D and SF-6D matter? Pain 2014, 155, 1996–2004. [Google Scholar] [CrossRef] [PubMed]
- Johannesson, M.; Diderichsen, F. Swedish population health-related quality of life using the EQ-5D. Qual. Life Res. 2001, 10, 621–635. [Google Scholar]
- Golicki, D.; Niewada, M.; Jakubczyk, M.; Wrona, W.; Hermanowski, T. Self-assessed health status in Poland: EQ-5D findings from the Polish valuation study. Value Health 2010, 11, 276–281. [Google Scholar] [CrossRef]
- Kontodimopoulos, N.; Pappa, E.; Niakas, D.; Yfantopoulos, J.; Dimitrakaki, C.; Tountas, Y. Validity of the EuroQoL (EQ-5D) instrument in a Greek general population. Value Health J. Int. Soc. Pharm. Outcomes Res. 2008, 11, 1162–1169. [Google Scholar] [CrossRef] [PubMed]
- Lubetkin, E.I.; Jia, H.; Franks, P.; Gold, M.R. Relationship among sociodemographic factors, clinical conditions, and health-related quality of life: Examining the EQ-5D in the U.S. general population. Qual. Life Res. 2005, 14, 2187–2196. [Google Scholar] [CrossRef] [PubMed]
- Fu, A.Z.; Kattan, M.W. Racial and ethnic differences in preference-based health status measure. Curr. Med. Res. Opin. 2006, 22, 2439–2448. [Google Scholar] [CrossRef] [PubMed]
- Bowling, A.; Bond, M.; Jenkinson, C.; Lamping, D.L. Short Form 36 (SF-36) Health Survey questionnaire: which normative data should be used? Comparisons between the norms provided by the Omnibus Survey in Britain, the Health Survey for England and the Oxford Healthy Life Survey. J. Public Health Med. 1999, 21, 255–270. [Google Scholar] [CrossRef] [PubMed]
- Weinberger, M.; Oddone, E.Z.; Samsa, G.P.; Landsman, P.B. Are health-related quality-of-life measures affected by the mode of administration? J. Clin. Epidemiol. 1996, 49, 135–140. [Google Scholar] [CrossRef]
- Keogh, E. Sex Differences in Pain. Behav. Brain Sci. 1997, 20, 764–765. [Google Scholar]
- Fillingim, R.B. Sex, gender, and pain: Women and men really are different. Curr. Pain Headache Rep. 2000, 4, 24–30. [Google Scholar] [CrossRef]
- Zhang, N.J.; Guo, M.; Zheng, X. China: Awakening Giant Developing Solutions to Population Aging. Gerontologist 2012, 52, 589–596. [Google Scholar] [CrossRef] [PubMed]
- National Bureau of Statistics of China, Bulletin of China’s Sixth National Population Census in 2010 (No. 1). Chin. J. Fam. Plan. 2011, 511–512.
- World Health Organization. Global Status Report on Noncommunicable Diseases 2014; WHO: Geneva, Switzerland, 2015. [Google Scholar]
- World Health Organization. Global Status Report on Noncommunicable Diseases 2010; WHO: Geneva, Switzerland, 2011. [Google Scholar]
- Wang, S.; Marquez, P.; Langenbrunner, J.; Niessen, L.; Suhrcke, M.; Song, F. Toward a Healthy and Harmonious Life in China: Stemming the Rising Tide of Non-Communicable Diseases; The World Bank: Washington, DC, USA, 2012. [Google Scholar]
- Liu, R.; Liu, Y.; Song, L.; Fu, H.; Yu, J.; Gao, Q.; Ou, F. The canonical correlation analysis between the quality of life and health of in urban poor population. Chin. J. Health Stat. 2005, 4, 244–256. [Google Scholar]
- Fu, H.; Liu, Y.; Guo, J.; Sun, W.; Jiao, T.; Song, L. Study on quality of life and its influential factors of urban poor people. Chin. J. Public Health 2004, 3, 87–88. [Google Scholar]
- Ou, F.; Ding, H.; Shuang; Gao, Q.; Hu, L.; Wu, X.; Liu, Y. The structural equation model of influence factors on the quality of life of urban poor population. Chin. J. Publ. Heal. 2012, 6, 867–868. [Google Scholar]
- Liu, R.; Liu, Y.; Fu, H.; Yu, J.; Ou, F.; Gao, Q.; Dong, G.; Lu, X. Multivariate analysis of variance and synthetical evaluation on quality of life in new urban poverty people. Chin. J. Publ. Heal. 2005, 8, 961–962. [Google Scholar]
- Gao, Q.; Fu, H.; Liu, Y.; Huang, D.; Jiaotian, Z.; Song, L.; Yu, J.; Liu, R. A survey on the quality of life of the new urban poverty in Shenyang. Chin. J. Dis. Control Prev. 2005, 5, 34–37. [Google Scholar]
- Zhou, Z.; Zhou, Z.; Li, D.; Wang, D.; Shi, C.; Shen, C.; Fang, Y.; Gao, J.; Chen, G. Analyzing the Health-related Quality of Life of Urban and Rural Residents in Shaanxi: Estimation Based on the EQ-5D Value Sets. Chin. Health Econ. 2015, 34, 13–16. [Google Scholar]
- Mcqueen, D.V.; Wismar, M.; Lin, V.; Jones, C.M.; Davies, M. Intersectoral Governance for Health in All Policies: Structures, actions and experiences. Rev. Direito Sanit. 2012, 26, 3–22. [Google Scholar]
- Shankardass, K. Strengthening the implementation of Health in All Policies: A methodology for realist explanatory case studies. Health Policy Plan. 2015, 30, 462–473. [Google Scholar] [CrossRef] [PubMed]
- World Health Organization. Global Health Risks: Mortality and Burden of Disease Attributable to Selected Major Risks; WHO: Geneva, Switzerland, 2009. [Google Scholar]
- World Health Organization. Global Recommendations on Physical Activity for Health; WHO: Geneva, Switzerland, 2010. [Google Scholar]
- World Health Organization. World Health Report 2002: Reducing Risks, Promoting Healthy Life; WHO: Geneva, Switzerland, 2002. [Google Scholar]
- World Health Organization. Resolution WHA57.17. Global Strategy on Diet, Physical Activity and Health. In Fifty-Seventh World Health Assembly Decisions, Annexes; WHO: Geneva, Switzerland, 2004. [Google Scholar]
- World Health Organization. Preventing Chronic Diseases: A Vital Investment; WHO: Geneva, Switzerland, 2005. [Google Scholar]
- World Health Organization. A Guide for Population-Based Approaches to Increasing Levels of Physical Activity: Implementation of the WHO Global Strategy on Diet, Physical Activity and Health; WHO: Geneva, Switzerland, 2007. [Google Scholar]
- World Health Organization. The Global Burden of Disease: 2004 Update; WHO: Geneva, Switzerland, 2008. [Google Scholar]
- Brazier, J.E.; Yang, Y.; Tsuchiya, A.; Rowen, D.L. A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Eur. J. Health Econ. 2010, 11, 215–225. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Longworth, L.; Yang, Y.; Young, T.; Mulhern, B.; Hernández, A.M.; Mukuria, C.; Rowen, D.; Tosh, J.; Tsuchiya, A.; Evans, P. Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: A systematic review, statistical modelling and survey. Health Technol. Assess. 2014, 18, 1–224. [Google Scholar] [CrossRef] [PubMed]
Characteristics of Respondents | EQ-5D-3L Index | EQ-5D VAS | |||||||
---|---|---|---|---|---|---|---|---|---|
N (%) | Mean (SD) | Ceiling Effect †† (%) | p (t/F) | p (M-W/K-W) | Mean (SD) | Ceiling Effect †† (%) | p (t/F) | p (M-W/K-W) | |
Total | 11523 (100.0) | 0.959 (0.124) | 85.05 | 79.60 (15.70) | 12.51 | ||||
Age (year) | |||||||||
18–29 | 1742 (15.1) | 0.993 (0.053) | 97.47 | 88.42 (10.22) | 23.25 | ||||
30–39 | 2467 (21.4) | 0.982 (0.080) | 91.93 | 84.43 (12.97) | 17.67 | ||||
40–49 | 2862 (24.8) | 0.970 (0.093) | 86.37 | 80.43 (14.65) | 12.33 | ||||
50–59 | 2494 (21.6) | 0.952 (0.132) | 81.68 | 75.74 (15.92) | 7.42 | ||||
60–69 | 1222 (10.6) | 0.912 (0.184) | 71.69 | 70.99 (16.35) | 4.09 | ||||
70+ | 736 (6.4) | 0.865 (0.220) | 61.01 | 0.000 | 0.000 | 66.73 (17.57) | 1.77 | 0.000 | 0.000 |
Sex | |||||||||
Male | 5628 (48.8) | 0.962 (0.122) | 86.50 | 80.57 (15.41) | 13.66 | ||||
Female | 5895 (51.2) | 0.957 (0.126) | 83.66 | 0.033 | 0.000 | 78.68 (15.92) | 11.42 | 0.000 | 0.000 |
Ethnicity | |||||||||
Han | 10973 (95.2) | 0.960 (0.123) | 85.17 | 79.58 (15.68) | 12.30 | ||||
Others | 550 (4.8) | 0.948 (0.148) | 82.55 | 0.053 | 0.063 | 80.13 (16.11) | 16.73 | 0.424 | 0.239 |
Residence | |||||||||
Urban | 4631 (40.2) | 0.955 (0.131) | 83.01 | 78.49 (15.59) | 8.83 | ||||
Rural | 6892 (59.8) | 0.962 (0.120) | 86.42 | 0.001 | 0.000 | 80.35 (15.73) | 14.99 | 0.000 | 0.000 |
Education | |||||||||
Below primary school | 931 (8.1) | 0.896 (0.191) | 65.95 | 68.47 (17.89) | 4.08 | ||||
Primary school | 3037 (26.4) | 0.944 (0.145) | 80.77 | 76.92 (16.38) | 10.11 | ||||
Junior middle school | 5339 (46.3) | 0.971 (0.105) | 88.35 | 81.39 (14.69) | 14.67 | ||||
Senior middle school | 1693 (14.7) | 0.977 (0.089) | 90.31 | 83.12 (13.67) | 15.00 | ||||
College and above | 523 (4.5) | 0.988 (0.055) | 93.12 | 0.000 | 0.000 | 85.39 (11.36) | 11.47 | 0.000 | 0.000 |
Housing | |||||||||
Flat/apartment | 2196 (19.1) | 0.962 (0.123) | 85.56 | 80.08 (14.77) | 8.24 | ||||
Brick bungalow | 6697 (58.1) | 0.962 (0.120) | 86.02 | 80.13 (15.37) | 14.02 | ||||
Mud-brick bungalow | 2556 (22.2) | 0.951 (0.135) | 82.63 | 77.89 (17.16) | 12.32 | ||||
Other † | 74 (0.6) | 0.902 (0.171) | 64.86 | 0.000 | 0.000 | 77.09 (15.31) | 9.46 | 0.000 | 0.000 |
Officially recorded poverty | |||||||||
Yes | 1390 (12.1) | 0.910 (0.175) | 69.42 | 72.44 (18.36) | 7.70 | ||||
No | 10133 (87.9) | 0.966 (0.114) | 87.19 | 0.000 | 0.000 | 80.59 (15.04) | 13.17 | 0.000 | 0.000 |
Marital status | |||||||||
Never married | 818 (7.1) | 0.989 (0.072) | 95.84 | 88.28 (11.45) | 24.82 | ||||
Married | 9905 (86.0) | 0.961 (0.120) | 85.38 | 79.57 (15.49) | 12.08 | ||||
Divorced | 182 (1.6) | 0.962 (0.094) | 81.87 | 79.16 (14.86) | 9.34 | ||||
Widowed | 618 (5.4) | 0.888 (0.203) | 66.34 | 0.000 | 0.000 | 68.77 (17.17) | 4.05 | 0.000 | 0.000 |
Employment | |||||||||
Employed | 7287 (63.2) | 0.975 (0.091) | 89.65 | 82.13 (14.55) | 15.74 | ||||
Retired | 1266 (11.0) | 0.930 (0.169) | 76.15 | 74.15 (15.86) | 4.66 | ||||
Unemployed | 2970 (25.8) | 0.932 (0.161) | 77.54 | 0.000 | 0.000 | 75.73 (16.93) | 7.95 | 0.000 | 0.000 |
Health insurance | |||||||||
Yes | 8548 (74.2) | 0.962 (0.121) | 85.86 | 80.03 (15.56) | 13.27 | ||||
No | 2975 (25.8) | 0.952 (0.135) | 82.72 | 0.000 | 0.000 | 78.38 (16.03) | 10.35 | 0.000 | 0.000 |
Chronic conditions (over the past six months) | |||||||||
Yes | 2517 (21.8) | 0.872 (0.208) | 57.77 | 66.85 (17.22) | 2.15 | ||||
No | 9006 (78.2) | 0.984 (0.071) | 92.67 | 0.000 | 0.000 | 83.17 (13.21) | 15.41 | 0.000 | 0.000 |
Regular weekly physical activities | |||||||||
Yes | 2160 (18.7) | 0.965 (0.095) | 83.43 | 79.60 (14.58) | 9.86 | ||||
No | 9363 (81.3) | 0.958 (0.130) | 85.42 | 0.058 | 0.084 | 79.61 (15.95) | 13.13 | 0.990 | 0.216 |
Mobility | Self-Care | Usual Activities | Pain/Discomfort | Anxiety/Depression | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
No %/N | Some %/N | Extreme %/N | No %/N | Some %/N | Extreme %/N | No %/N | Some %/N | Extreme %/N | No %/N | Some %/N | Extreme %/N | No %/N | Some %/N | Extreme %/N | |
Total | 94.6 | 4.9 | 0.5 | 96.3 | 3.1 | 0.5 | 94.7 | 4.5 | 0.9 | 87.9 | 11.4 | 0.7 | 92.8 | 6.6 | 0.6 |
Sex | |||||||||||||||
Male | 94.2 | 5.3 | 0.5 | 96.2 | 3.2 | 0.6 | 94.6 | 4.5 | 1.0 | 89.5 | 10.0 | 0.5 | 93.8 | 5.7 | 0.5 |
Female | 94.9 | 4.6 | 0.5 | 96.5 | 3.0 | 0.5 | 94.7 | 4.5 | 0.8 | 86.4 | 12.7 | 0.9 | 91.8 | 7.5 | 0.7 |
Age (year) | |||||||||||||||
18–29 | 99.1 | 0.7 | 0.1 | 99.4 | 0.6 | 0.0 | 99.1 | 0.7 | 0.2 | 98.4 | 1.5 | 0.1 | 98.6 | 1.3 | 0.2 |
30–39 | 98.1 | 1.7 | 0.3 | 99.1 | 0.8 | 0.2 | 98.1 | 1.6 | 0.3 | 93.8 | 5.9 | 0.3 | 96.1 | 3.5 | 0.4 |
40–49 | 96.8 | 2.9 | 0.3 | 98.2 | 1.6 | 0.2 | 97.2 | 2.4 | 0.4 | 89.8 | 10.0 | 0.2 | 93.3 | 6.4 | 0.3 |
50–59 | 93.6 | 5.9 | 0.5 | 95.9 | 3.5 | 0.6 | 94.1 | 4.9 | 1.0 | 84.7 | 14.4 | 0.9 | 91.9 | 7.5 | 0.7 |
60–69 | 88.1 | 10.7 | 1.2 | 92.0 | 6.3 | 1.7 | 87.3 | 10.2 | 2.5 | 75.2 | 22.8 | 2.0 | 85.6 | 12.8 | 1.6 |
70+ | 77.3 | 21.1 | 1.6 | 81.7 | 15.9 | 2.4 | 76.8 | 19.8 | 3.4 | 68.1 | 29.2 | 2.7 | 81.4 | 17.0 | 1.6 |
Ethnicity | |||||||||||||||
Han | 94.7 | 4.8 | 0.5 | 96.4 | 3.0 | 0.5 | 94.8 | 4.4 | 0.8 | 88.0 | 11.3 | 0.7 | 92.8 | 6.6 | 0.6 |
Others | 91.3 | 7.6 | 1.1 | 94.7 | 4.4 | 0.9 | 92.5 | 5.8 | 1.6 | 86.2 | 13.3 | 0.5 | 93.1 | 5.6 | 1.3 |
Residence | |||||||||||||||
Urban | 94.1 | 5.4 | 0.5 | 96.0 | 3.2 | 0.8 | 94.6 | 4.4 | 1.0 | 87.1 | 12.0 | 0.9 | 91.2 | 8.0 | 0.8 |
Rural | 94.9 | 4.6 | 0.5 | 96.6 | 3.0 | 0.4 | 94.7 | 4.5 | 0.8 | 88.5 | 10.9 | 0.6 | 93.9 | 5.6 | 0.5 |
Education | |||||||||||||||
Below primary school | 84.3 | 14.6 | 1.1 | 88.5 | 10.1 | 1.4 | 84.6 | 13.2 | 2.1 | 71.3 | 26.2 | 2.5 | 83.7 | 14.8 | 1.5 |
Primary school | 92.4 | 6.9 | 0.7 | 94.7 | 4.5 | 0.8 | 91.7 | 6.9 | 1.4 | 83.7 | 15.3 | 0.9 | 90.6 | 8.6 | 0.8 |
Junior middle school | 96.3 | 3.3 | 0.4 | 97.7 | 1.9 | 0.4 | 96.7 | 2.7 | 0.6 | 90.9 | 8.6 | 0.5 | 94.4 | 5.1 | 0.5 |
Senior middle school | 97.3 | 2.5 | 0.2 | 98.2 | 1.5 | 0.2 | 97.5 | 2.2 | 0.3 | 92.9 | 6.8 | 0.4 | 95.4 | 4.3 | 0.4 |
College and above | 98.7 | 1.3 | 0.0 | 99.6 | 0.2 | 0.2 | 99.2 | 0.4 | 0.4 | 95.8 | 4.2 | 0.0 | 97.1 | 2.9 | 0.0 |
Housing | |||||||||||||||
Flat/apartment | 95.1 | 4.3 | 0.5 | 97.0 | 2.2 | 0.8 | 96.1 | 3.1 | 0.9 | 89.1 | 10.0 | 0.9 | 92.9 | 6.5 | 0.6 |
Brick bungalow | 94.8 | 4.7 | 0.5 | 96.6 | 2.9 | 0.5 | 94.9 | 4.2 | 0.8 | 88.9 | 10.5 | 0.6 | 93.3 | 6.2 | 0.6 |
Mud-brick bungalow | 93.6 | 5.9 | 0.5 | 95.2 | 4.3 | 0.5 | 92.9 | 6.2 | 0.9 | 84.7 | 14.4 | 0.9 | 91.8 | 7.6 | 0.6 |
Other † | 90.5 | 9.5 | 0.0 | 94.6 | 5.4 | 0.0 | 87.8 | 9.5 | 2.7 | 73.0 | 23.0 | 4.1 | 81.1 | 12.2 | 6.8 |
Officially recorded poverty | |||||||||||||||
Yes | 87.0 | 12.3 | 0.7 | 90.9 | 7.8 | 1.3 | 87.1 | 11.2 | 1.8 | 76.8 | 21.9 | 1.4 | 82.2 | 16.0 | 1.9 |
No | 95.6 | 3.9 | 0.5 | 97.1 | 2.5 | 0.4 | 95.7 | 3.6 | 0.7 | 89.5 | 9.9 | 0.6 | 94.3 | 5.3 | 0.5 |
Marital status | |||||||||||||||
Never married | 98.5 | 1.2 | 0.2 | 99.0 | 0.7 | 0.2 | 98.7 | 0.9 | 0.5 | 97.3 | 2.6 | 0.1 | 98.2 | 1.5 | 0.4 |
Married | 94.9 | 4.6 | 0.5 | 96.7 | 2.8 | 0.5 | 95.1 | 4.2 | 0.8 | 88.2 | 11.1 | 0.6 | 93.0 | 6.4 | 0.6 |
Divorced | 96.7 | 3.3 | 0.0 | 96.7 | 3.3 | 0.0 | 96.2 | 3.8 | 0.0 | 85.7 | 14.3 | 0.0 | 90.1 | 9.9 | 0.0 |
Widowed | 82.8 | 16.5 | 0.6 | 87.4 | 10.4 | 2.3 | 82.4 | 14.6 | 3.1 | 71.2 | 25.4 | 3.4 | 83.5 | 14.7 | 1.8 |
Employment | |||||||||||||||
Employed | 97.1 | 2.6 | 0.3 | 98.2 | 1.7 | 0.2 | 97.0 | 2.6 | 0.4 | 91.4 | 8.3 | 0.3 | 95.6 | 4.1 | 0.3 |
Retired | 89.5 | 9.6 | 0.9 | 93.1 | 5.4 | 1.5 | 90.4 | 7.6 | 2.1 | 81.0 | 17.5 | 1.6 | 89.7 | 9.1 | 1.2 |
Unemployed | 90.5 | 8.8 | 0.8 | 93.2 | 5.7 | 1.1 | 90.8 | 7.6 | 1.6 | 82.4 | 16.3 | 1.3 | 87.1 | 11.6 | 1.2 |
Medical insurance | |||||||||||||||
Yes | 94.8 | 4.7 | 0.5 | 96.6 | 3.0 | 0.5 | 94.9 | 4.3 | 0.8 | 88.4 | 11.0 | 0.6 | 93.6 | 5.8 | 0.6 |
No | 93.8 | 5.6 | 0.5 | 95.7 | 3.5 | 0.8 | 93.9 | 5.1 | 0.9 | 86.6 | 12.4 | 0.9 | 90.5 | 8.7 | 0.8 |
Chronic conditions (over the past six months) | |||||||||||||||
Yes | 82.8 | 15.5 | 1.7 | 87.6 | 10.4 | 2.0 | 82.0 | 14.9 | 3.0 | 63.2 | 33.9 | 2.9 | 79.0 | 18.7 | 2.3 |
No | 97.8 | 2.0 | 0.1 | 98.8 | 1.1 | 0.1 | 98.2 | 1.6 | 0.3 | 94.9 | 5.0 | 0.1 | 96.7 | 3.2 | 0.2 |
Regular weekly physical activities | |||||||||||||||
Yes | 96.0 | 3.9 | 0.1 | 98.0 | 1.8 | 0.2 | 96.0 | 3.7 | 0.3 | 87.1 | 12.5 | 0.3 | 93.0 | 6.8 | 0.3 |
No | 94.2 | 5.2 | 0.6 | 96.0 | 3.4 | 0.6 | 94.3 | 4.7 | 1.0 | 88.1 | 11.1 | 0.8 | 92.8 | 6.5 | 0.7 |
Mobility OR (95% CI) | Self-Care OR (95% CI) | Usual Activities OR (95% CI) | Pain/Discomfort OR (95% CI) | Anxiety/Depression OR (95% CI) | EQ-5D-3L Index Beta (95% CI) | |
---|---|---|---|---|---|---|
Sex | ||||||
Male | Reference | Reference | Reference | Reference | Reference | Reference |
Female | 0.6 (0.5, 0.7) ** | 0.7 (0.5, 0.9) ** | 0.7 (0.6, 0.9) ** | 1.1 (1.0, 1.3) | 1.1 (0.9, 1.3) | 0.00 (0.00, 0.01) |
Age (year) | ||||||
18–29 | Reference | Reference | Reference | Reference | Reference | Reference |
30–39 | 1.7 (0.9, 3.2) | 1.0 (0.5, 2.2) | 1.4 (0.8, 2.6) | 2.8 (1.8, 4.4) ** | 1.8 (1.1, 2.9) * | 0.00 (−0.01, 0.01) |
40–49 | 2.0 (1.1, 3.7) * | 1.4 (0.7, 2.8) | 1.5 (0.8, 2.7) | 3.7 (2.4, 5.6) ** | 2.4 (1.5, 3.8) ** | 0.00 (−0.01, 0.01) |
50–59 | 3.1 (1.7, 5.5) ** | 2.5 (1.3, 5.0) ** | 2.3 (1.3, 4.1) ** | 4.3 (2.8, 6.5) ** | 2.3 (1.4, 3.6) ** | −0.01 (−0.02, 0.00) * |
60–69 | 3.4 (1.8, 6.4) ** | 3.0 (1.5, 6.2) ** | 3.2 (1.7, 5.8) ** | 4.8 (3.0, 7.5) ** | 2.6 (1.6, 4.3) ** | −0.03 (−0.04, −0.02) ** |
70+ | 5.9 (3.1, 11.1) ** | 6.7 (3.2, 14.2) | 5.7 (3.0, 10.7) ** | 5.7 (3.5, 9.3) ** | 2.9 (1.7, 4.9) ** | −0.06 (−0.07, −0.05) ** |
Ethnicity | ||||||
Han | Reference | Reference | Reference | Reference | Reference | Reference |
Others | 1.6 (1.1, 2.3) ** | 0.7 (0.5, 1.1) | 1.3 (0.9, 1.9) | 1.1 (0.9, 1.5) | 0.9 (0.6, 1.3) | −0.01 (−0.02, −0.00) |
Residence | ||||||
Urban | Reference | Reference | Reference | Reference | Reference | Reference |
Rural | 1.6 (1.2, 2.3) ** | 1.2 (0.8, 1.8) | 1.8 (1.3, 2.5) ** | 1.2 (0.9, 1.5) | 1.0 (0.7, 1.3) | 0.01 (0.00, 0.01) |
Education | ||||||
Below primary school | Reference | Reference | Reference | Reference | Reference | Reference |
Primary school | 1.0 (0.8, 1.3) | 1.1 (0.8, 1.5) | 1.3 (1.0, 1.7) | 0.9 (0.8, 1.2) | 1.0 (0.8, 1.3) | 0.00 (0.00, 0.01) |
Junior middle school | 0.7 (0.5, 0.9) * | 0.8 (0.6, 1.2) | 0.8 (0.6, 1.1) | 0.7 (0.6, 0.9) ** | 0.8 (0.6, 1.0) | 0.01 (0.00, 0.02) ** |
Senior middle school | 0.6 (0.4, 0.9) * | 0.8 (0.5, 1.2) | 0.8 (0.5, 1.2) | 0.6 (0.5, 0.8) ** | 0.7 (0.5, 0.9) * | 0.01 (0.00, 0.02) * |
College and above | 0.4 (0.2, 1.0) | 0.3 (0.1, 1.1) | 0.4 (0.1, 1.1) | 0.5 (0.3, 0.8) ** | 0.6 (0.3, 1.1) | 0.01 (0.00, 0.03) |
Housing | ||||||
Flat/apartment | Reference | Reference | Reference | Reference | Reference | Reference |
Brick bungalow | 0.9 (0.7, 1.2) | 1.0 (0.7, 1.4) | 1.2 (0.9, 1.6) | 1.1 (0.9, 1.4) | 1.0 (0.7, 1.2) | 0.00 (0.00, 0.01) |
Mud-brick bungalow | 0.9 (0.6, 1.3) | 1.2 (0.8, 1.9) | 1.3 (0.9, 2.0) | 1.4 (1.1, 1.8) * | 1.1 (0.8, 1.5) | 0.00 (−0.01, 0.01) |
Other † | 1.3 (0.5, 3.2) | 1.2 (0.4, 3.7) | 2.4 (1.0, 5.7) * | 3.2 (1.7, 6.0) ** | 2.8 (1.4, 5.6) ** | −0.04 (−0.07, −0.02) ** |
Officially recorded poverty | ||||||
No | Reference | Reference | Reference | Reference | Reference | Reference |
Yes | 2.4 (1.9, 3.0) ** | 2.2 (1.7, 2.8) ** | 2.5 (2.0, 3.1) ** | 2.0 (1.7, 2.4) ** | 2.6 (2.1, 3.1) ** | −0.04 (−0.04, −0.03) ** |
Marital status | ||||||
Never married | Reference | Reference | Reference | Reference | Reference | Reference |
Married | 1.2 (0.6, 2.3) | 1.1 (0.5, 2.5) | 1.3 (0.7, 2.6) | 1.4 (0.8, 2.2) | 1.5 (0.8, 2.6) | 0.00 (−0.01, 0.01) |
Divorced | 0.7 (0.2, 2.1) | 1.3 (0.4, 4.2) | 1.1 (0.4, 3.0) | 1.8 (0.9, 3.5) | 1.7 (0.8, 3.7) | 0.00 (−0.02, 0.02) |
Widowed | 1.4 (0.7, 2.8) | 1.2 (0.5, 2.9) | 1.5 (0.7, 3.2) | 1.4 (0.8, 2.4) | 1.4 (0.7, 2.6) | −0.01 (−0.02, 0.00) |
Employment | ||||||
Employed | Reference | Reference | Reference | Reference | Reference | Reference |
Retired | 3.3 (2.3, 4.8) ** | 2.7 (1.7, 4.1) ** | 3.0 (2.0, 44) ** | 1.6 (1.2, 2.1) ** | 1.6 (1.2, 2.2) ** | −0.02 (−0.02, −0.01) ** |
Unemployed | 2.7 (2.1, 3.5) ** | 2.4 (1.8, 3.3) ** | 2.4 (1.8, 3.1) ** | 1.6 (1.4, 2.0) ** | 2.2 (1.7, 2.7) ** | −0.03 (−0.03, 0.02) ** |
Health insurance | ||||||
No | Reference | Reference | Reference | Reference | Reference | Reference |
Yes | 1.0 (0.7, 1.2) | 1.0 (0.7, 1.4) | 0.9 (0.7, 1.1) | 1.1 (0.9, 1.3) | 1.0 (0.8, 1.3) | 0.00 (0.00, 0.01) |
Chronic conditions | ||||||
No | Reference | Reference | Reference | Reference | Reference | Reference |
Yes | 6.0 (5.0, 7.3) ** | 6.9 (5.4, 8.8) ** | 7.6 (6.2, 9.2) ** | 7.4 (6.5, 8.5) ** | 5.6 (4.7, 6.6) ** | −0.09 (−0.10, −0.09) ** |
Regular weekly physical activities | ||||||
No | Reference | Reference | Reference | Reference | Reference | Reference |
Yes | 0.4 (0.3, 0.6) ** | 0.3 (0.2, 0.4) ** | 0.5 (0.4, 0.6) ** | 1.0 (0.8, 1.2) | 0.8 (0.6, 1.0) * | 0.02 (0.01, 0.02) ** |
Cox and Snell R2 | 0.096 | 0.079 | 0.104 | 0.155 | 0.090 | |
Nagelkerke R2 | 0.278 | 0.293 | 0.306 | 0.297 | 0.222 | |
R2 | 0.186 | |||||
Adjusted R2 | 0.184 |
© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Huang, W.; Yu, H.; Liu, C.; Liu, G.; Wu, Q.; Zhou, J.; Zhang, X.; Zhao, X.; Shi, L.; Xu, X. Assessing Health-Related Quality of Life of Chinese Adults in Heilongjiang Using EQ-5D-3L. Int. J. Environ. Res. Public Health 2017, 14, 224. https://doi.org/10.3390/ijerph14030224
Huang W, Yu H, Liu C, Liu G, Wu Q, Zhou J, Zhang X, Zhao X, Shi L, Xu X. Assessing Health-Related Quality of Life of Chinese Adults in Heilongjiang Using EQ-5D-3L. International Journal of Environmental Research and Public Health. 2017; 14(3):224. https://doi.org/10.3390/ijerph14030224
Chicago/Turabian StyleHuang, Weidong, Hongjuan Yu, Chaojie Liu, Guoxiang Liu, Qunhong Wu, Jin Zhou, Xin Zhang, Xiaowen Zhao, Linmei Shi, and Xiaoxue Xu. 2017. "Assessing Health-Related Quality of Life of Chinese Adults in Heilongjiang Using EQ-5D-3L" International Journal of Environmental Research and Public Health 14, no. 3: 224. https://doi.org/10.3390/ijerph14030224