Skip to main content

Advertisement

Log in

Association between knee symptoms, change in knee symptoms over 6–9 years, and SF-6D health state utility among middle-aged Australians

  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

Objectives

Health state utilities (HSUs) are an input metric for estimating quality-adjusted life-years (QALY) in cost–utility analyses. Currently, there is a paucity of data on association of knee symptoms with HSUs for middle-aged populations. We aimed to describe the association of knee symptoms and change in knee symptoms with SF-6D HSUs and described the distribution of HSUs against knee symptoms’ severity.

Methods

Participants (36–49-years) were selected from the third follow-up (completed 2019) of Australian Childhood Determinants of Adult Health study. SF-6D HSUs were generated from the participant-reported SF-12. Association between participant-reported WOMAC knee symptoms’ severity, change in knee symptoms over 6–9 years, and HSUs were evaluated using linear regression models.

Results

For the cross-sectional analysis, 1,567 participants were included; mean age 43.5 years, female 54%, BMI ± SD 27.18 ± 5.31 kg/m2. Mean ± SD HSUs for normal, moderate, and severe WOMAC scores were 0.820 ± 0.120, 0.800 ± 0.120, and 0.740 ± 0.130, respectively. A significant association was observed between worsening knee symptoms and HSUs in univariable and multivariable analyses after adjustment (age and sex). HSU decrement for normal-to-severe total-WOMAC and WOMAC-pain was − 0.080 (95% CI − 0.100 to − 0.060, p < 0.01) and − 0.067 (− 0.085 to − 0.048, p < 0.01), exceeding the mean minimal clinically important difference (0.04). Increase in knee pain over 6–9 years was associated with a significant reduction in HSU.

Conclusion

In a middle-aged population-based sample, there was an independent negative association between worse knee symptoms and SF-6D HSUs. Our findings may be used by decision-makers to define more realistic and conservative baseline and ongoing HSU values when assessing QALY changes associated with osteoarthritis interventions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Woolf, A. D., & Pfleger, B. (2003). Burden of major musculoskeletal conditions. Bulletin of the World Health Organization, 81(9), 646–656

    PubMed  PubMed Central  Google Scholar 

  2. Muraki, S., Akune, T., Oka, H., En-yo, Y., Yoshida, M., Saika, A., et al. (2010). Impact of knee and low back pain on health-related quality of life in Japanese women: The Research on Osteoarthritis Against Disability (ROAD). Modern Rheumatology., 20(5), 444–451

    Article  PubMed  Google Scholar 

  3. Nguyen, U. S. D. T., Zhang, Y., Zhu, Y., Niu, J., Zhang, B., & Felson, D. T. (2011). Increasing prevalence of knee pain and symptomatic knee osteoarthritis: Survey and cohort data. Annals of Internal Medicine, 155(11), 725–732

    Article  PubMed  PubMed Central  Google Scholar 

  4. Jinks, C., Jordan, K., Ong, B. N., & Croft, P. (2004). A brief screening tool for knee pain in primary care (KNEST). 2. Results from a survey in the general population aged 50 and over. Rheumatology (Oxford), 43(1), 55–61

    Article  CAS  Google Scholar 

  5. Health AIo, Welfare. (2019). Osteoarthritis. AIHW.

  6. Vos, T., Lim, S. S., Abbafati, C., Abbas, K. M., Abbasi, M., Abbasifard, M., et al. (2020). Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10258), 1204–1222

    Article  Google Scholar 

  7. Gaskin, D. J., & Richard, P. (2012). The economic costs of pain in the United States. The Journal of Pain, 13(8), 715–724

    Article  PubMed  Google Scholar 

  8. Bindawas, S. M., Vennu, V., & Al, S. S. (2015). Differences in health-related quality of life among subjects with frequent bilateral or unilateral knee pain: Data from the Osteoarthritis Initiative study. Journal of Orthopaedic and Sports Physical Therapy, 45(2), 128–136

    Article  Google Scholar 

  9. Hunter, D. J., Nicolson, P. J. A., Little, C. B., Robbins, S. R., Wang, X., & Bennell, K. L. (2019). Developing strategic priorities in osteoarthritis research: Proceedings and recommendations arising from the 2017 Australian Osteoarthritis Summit. BMC Musculoskeletal Disorders, 20(1), 74

    Article  PubMed  PubMed Central  Google Scholar 

  10. Xie, F., Kovic, B., Jin, X., He, X., Wang, M., & Silvestre, C. (2016). Economic and humanistic burden of osteoarthritis: A systematic review of large sample studies. PharmacoEconomics, 34(11), 1087–1100

    Article  PubMed  Google Scholar 

  11. Arden, N., Blanco, F., Cooper, C., Guermazi, A., Hayashi, D., Hunter, D., et al. (2014). Atlas of osteoarthritis. (1st ed.). Springer Healthcare Communications.

    Google Scholar 

  12. Salaffi, F., Carotti, M., & Grassi, W. (2005). Health-related quality of life in patients with hip or knee osteoarthritis: Comparison of generic and disease-specific instruments. Clinical Rheumatology, 24(1), 29–37

    Article  PubMed  Google Scholar 

  13. Pang, J., Cao, Y. L., Zheng, Y. X., Gao, N. Y., Wang, X. Z., Chen, B., et al. (2015). Influence of pain severity on health-related quality of life in Chinese knee osteoarthritis patients. International Journal of Clinical and Experimental Medicine, 8(3), 4472–4479

    PubMed  PubMed Central  Google Scholar 

  14. Kiadaliri, A. A., Lamm, C. J., de Verdier, M. G., Engström, G., Turkiewicz, A., Lohmander, L. S., et al. (2016). Association of knee pain and different definitions of knee osteoarthritis with health-related quality of life: A population-based cohort study in southern Sweden. Health and Quality of Life Outcomes, 14(1), 121

    Article  PubMed  PubMed Central  Google Scholar 

  15. Törmälehto, S., Mononen, M. E., Aarnio, E., Arokoski, J. P., Korhonen, R. K., & Martikainen, J. (2018). Health-related quality of life in relation to symptomatic and radiographic definitions of knee osteoarthritis: Data from Osteoarthritis Initiative (OAI) 4-year follow-up study. Health and Quality of Life Outcomes, 16(1), 154

    Article  PubMed  PubMed Central  Google Scholar 

  16. Bindawas, S. M., Vennu, V., & Auais, M. (2015). Health-related quality of life in older adults with bilateral knee pain and back pain: Data from the Osteoarthritis Initiative. Rheumatology International, 35(12), 2095–2101

    Article  PubMed  PubMed Central  Google Scholar 

  17. Bellamy, N. (2002). WOMAC: A 20-year experiential review of a patient-centered self-reported health status questionnaire. Journal of Rheumatology, 29(12), 2473–2476

    Google Scholar 

  18. McConnell, S., Kolopack, P., & Davis, A. M. (2001). The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC): A review of its utility and measurement properties. Arthritis and Rheumatism, 45(5), 453–461

    Article  CAS  PubMed  Google Scholar 

  19. Xie, F., Pullenayegum, E. M., Li, S. C., Hopkins, R., Thumboo, J., & Lo, N. N. (2010). Use of a disease-specific instrument in economic evaluations: Mapping WOMAC onto the EQ-5D utility index. Value in Health, 13(8), 873–878

    Article  PubMed  Google Scholar 

  20. Kharroubi, S. A., Brazier, J. E., Roberts, J., & O’Hagan, A. (2007). Modelling SF-6D health state preference data using a nonparametric Bayesian method. Journal of Health Economics, 26(3), 597–612

    Article  PubMed  Google Scholar 

  21. Mulhern, B., Feng, Y., Shah, K., Janssen, M. F., Herdman, M., van Hout, B., et al. (2018). Comparing the UK EQ-5D-3L and English EQ-5D-5L value sets. PharmacoEconomics, 36(6), 699–713

    Article  PubMed  PubMed Central  Google Scholar 

  22. Richardson, J., Sinha, K., Iezzi, A., & Khan, M. A. (2014). Modelling utility weights for the Assessment of Quality of Life (AQoL)-8D. Quality of Life Research, 23(8), 2395–2404

    Article  PubMed  Google Scholar 

  23. Feeny, D., Furlong, W., Torrance, G. W., Goldsmith, C. H., Zhu, Z., DePauw, S., et al. (2002). Multiattribute and single-attribute utility functions for the health utilities index mark 3 system. Medical Care, 40(2), 113–128

    Article  PubMed  Google Scholar 

  24. Brazier, J. E., & Roberts, J. (2004). The estimation of a preference-based measure of health from the SF-12. Medical Care, 42, 851–859

    Article  PubMed  Google Scholar 

  25. Horsman, J., Furlong, W., Feeny, D., & Torrance, G. (2003). The Health Utilities Index (HUI®): Concepts, measurement properties and applications. Health and Quality of Life Outcomes, 1(1), 54

    Article  PubMed  PubMed Central  Google Scholar 

  26. Brooks R, Group E. (1996). EuroQol: The current state of play. Health Policy, 37(1), 53–72

    Article  Google Scholar 

  27. Edlin, R., McCabe, C., Hulme, C., Hall, P., & Wright, J. (2015). Cost effectiveness modelling for health technology assessment. Springer.

  28. Muennig, P., & Bounthavong, M. (2016). Cost-effectiveness analysis in health: A practical approach. Wiley.

  29. National Institute for Health and Care Excellence. (2015). Single technology appraisal: User guide for company evidence submission template-Process and methods-3 Cost effectiveness. National Institute for Health and Care Excellence. [updated 01 April 2017]. Process and methods [PMG24]. Retrieved from https://www.nice.org.uk/process/pmg24/chapter/cost-effectiveness#economic-analysis

  30. Government A. (2020). Quality-Adjusted-Life-Years (QALYs) Australia: The Department of Health. Retrieved from https://www1.health.gov.au/internet/publications/publishing.nsf/Content/illicit-pubs-needle-return-1-rep-toc~illicit-pubs-needle-return-1-rep-5~illicit-pubs-needle-return-1-rep-5-2

  31. Torrance, G. W., & Feeny, D. (1989). Utilities and quality-adjusted life years. International Journal of Technology Assessment in Health Care, 5(4), 559–575

    Article  CAS  PubMed  Google Scholar 

  32. Karmarkar, T. D., Maurer, A., Parks, M. L., Mason, T., Bejinez-Eastman, A., Harrington, M., et al. (2017). A fresh perspective on a familiar problem: Examining disparities in knee osteoarthritis using a Markov model. Medical Care, 55(12), 993

    Article  PubMed  PubMed Central  Google Scholar 

  33. Beck, J. R., & Pauker, S. G. (1983). The Markov process in medical prognosis. Medical Decision Making, 3(4), 419–458

    Article  CAS  PubMed  Google Scholar 

  34. Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: A practical guide. Medical Decision Making, 13(4), 322–338

    Article  CAS  PubMed  Google Scholar 

  35. Graves, N., Wloch, C., Wilson, J., Barnett, A., Sutton, A., Cooper, N., et al. (2016). A cost-effectiveness modelling study of strategies to reduce risk of infection following primary hip replacement based on a systematic review. Health Technology Assessment. https://doi.org/10.3310/hta20540

    Article  PubMed  Google Scholar 

  36. Clarke, P. M., Hayes, A. J., Glasziou, P. G., Scott, R., Simes, J., & Keech, A. C. (2009). Using the EQ-5D index score as a predictor of outcomes in patients with type 2 diabetes. Medical Care, 47(1), 61–68

    Article  PubMed  Google Scholar 

  37. Skinner, E. H., Denehy, L., Warrillow, S., & Hawthorne, G. (2013). Comparison of the measurement properties of the AQoL and SF-6D in critical illness. Critical Care and Resuscitation, 15(3), 205–212

    PubMed  Google Scholar 

  38. Zhao, T., Winzenberg, T., de Graaff, B., Aitken, D., Ahmad, H., & Palmer, A. J. (2020). A systematic review and meta-analysis of health state utility values for osteoarthritis-related conditions. Arthritis Care & Research. https://doi.org/10.1002/acr.24478

    Article  Google Scholar 

  39. Jinks, C., Jordan, K., & Croft, P. (2002). Measuring the population impact of knee pain and disability with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Pain, 100(1–2), 55–64

    Article  PubMed  Google Scholar 

  40. Wilkie, R., Peat, G., Thomas, E., & Croft, P. (2007). Factors associated with restricted mobility outside the home in community-dwelling adults ages fifty years and older with knee pain: An example of use of the International Classification of Functioning to investigate participation restriction. Arthritis and Rheumatism, 57(8), 1381–1389

    Article  PubMed  Google Scholar 

  41. Jinks, C., Jordan, K., & Croft, P. (2007). Osteoarthritis as a public health problem: The impact of developing knee pain on physical function in adults living in the community: (KNEST 3). Rheumatology (Oxford), 46(5), 877–881

    Article  CAS  Google Scholar 

  42. Fransen, M., Su, S., Harmer, A., Blyth, F. M., Naganathan, V., Sambrook, P., et al. (2013). A longitudinal study of knee pain in older men: Concord Health and Ageing in Men Project. Age and Ageing, 43(2), 206–212

    Article  PubMed  Google Scholar 

  43. Woo, J., Leung, J., & Lau, E. (2009). Prevalence and correlates of musculoskeletal pain in Chinese elderly and the impact on 4-year physical function and quality of life. Public Health, 123(8), 549–556

    Article  CAS  PubMed  Google Scholar 

  44. Venn, A. J., Thomson, R. J., Schmidt, M. D., Cleland, V. J., Curry, B. A., Gennat, H. C., et al. (2007). Overweight and obesity from childhood to adulthood: A follow-up of participants in the 1985 Australian Schools Health and Fitness Survey. Medical Journal of Australia, 186(9), 458–460

    Article  Google Scholar 

  45. Magnussen, C. G., Raitakari, O. T., Thomson, R., Juonala, M., Patel, D. A., Viikari, J. S., et al. (2008). Utility of currently recommended pediatric dyslipidemia classifications in predicting dyslipidemia in adulthood: evidence from the Childhood Determinants of Adult Health (CDAH) study, Cardiovascular Risk in Young Finns Study, and Bogalusa Heart Study. Circulation, 117(1), 32–42

    Article  PubMed  Google Scholar 

  46. Smith, K. J., Sanderson, K., McNaughton, S. A., Gall, S. L., Dwyer, T., & Venn, A. J. (2014). Longitudinal associations between fish consumption and depression in young adults. American Journal of Epidemiology, 179(10), 1228–1235

    Article  PubMed  Google Scholar 

  47. Tian, J., Gall, S., Patterson, K., Otahal, P., Blizzard, L., Patton, G., et al. (2019). Socioeconomic position over the life course from childhood and smoking status in mid-adulthood: Results from a 25-year follow-up study. BMC Public Health, 19(1), 169

    Article  PubMed  PubMed Central  Google Scholar 

  48. Tian, J., Venn, A. J., Blizzard, L., Patton, G. C., Dwyer, T., & Gall, S. L. (2016). Smoking status and health-related quality of life: A longitudinal study in young adults. Quality of Life Research, 25(3), 669–685

    Article  PubMed  Google Scholar 

  49. Antony, B., Jones, G., Venn, A., Cicuttini, F., March, L., Blizzard, L., et al. (2015). Association between childhood overweight measures and adulthood knee pain, stiffness and dysfunction: A 25-year cohort study. Annals of the Rheumatic Diseases, 74(4), 711–717

    Article  PubMed  Google Scholar 

  50. Obese, H. (1998). Body Mass Index (BMI). Obesity Research, 6(2), 51S-209S

    Google Scholar 

  51. World Health Organization. (2000). Obesity: Preventing and managing the global epidemic. World Health Organization.

  52. Heintjes, E., Bierma-Zeinstra, S., Berger, M., & Koes, B. (2008). Lysholm scale and WOMAC index were responsive in prospective cohort of young general practice patients. Journal of Clinical Epidemiology, 61(5), 481–488

    Article  CAS  PubMed  Google Scholar 

  53. Antony, B., Venn, A., Cicuttini, F., March, L., Blizzard, L., Dwyer, T., et al. (2016). Correlates of knee bone marrow lesions in younger adults. Arthritis Research & Therapy, 18, 31

    Article  CAS  Google Scholar 

  54. Zhang, B., Lin, H., Hunter, D. J., Neogi, T., Wise, B., Choy, E., et al. (2009). A multistate transition model for osteoarthritis pain change. Communications in Statistics – Theory and Methods, 38(18), 3297–3306

    Article  PubMed  PubMed Central  Google Scholar 

  55. Obradovic, M., Lal, A., & Liedgens, H. (2013). Validity and responsiveness of EuroQol-5 dimension (EQ-5D) versus Short Form-6 dimension (SF-6D) questionnaire in chronic pain. Health and Quality of Life Outcomes, 11(1), 110

    Article  PubMed  PubMed Central  Google Scholar 

  56. Campbell, J. A., Jelinek, G. A., Weiland, T. J., Nag, N., Neate, S. L., Palmer, A. J., et al. (2020). SF-6D health state utilities for lifestyle, sociodemographic and clinical characteristics of a large international cohort of people with multiple sclerosis. Quality of Life Research, 29(9), 2509–2527

    Article  PubMed  Google Scholar 

  57. Dritsaki, M., Petrou, S., Williams, M., & Lamb, S. E. (2017). An empirical evaluation of the SF-12, SF-6D, EQ-5D and Michigan Hand Outcome Questionnaire in patients with rheumatoid arthritis of the hand. Health and Quality of Life Outcomes, 15(1), 20

    Article  PubMed  PubMed Central  Google Scholar 

  58. Jayadevappa, R., Cook, R., & Chhatre, S. (2017). Minimal important difference to infer changes in health-related quality of life—A systematic review. Journal of Clinical Epidemiology, 89, 188–198

    Article  PubMed  Google Scholar 

  59. Walters, S. J., & Brazier, J. E. (2005). Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D. Quality of Life Research, 14(6), 1523–1532

    Article  PubMed  Google Scholar 

  60. Luo, N., Johnson, J. A., & Coons, S. J. (2010). Using instrument-defined health state transitions to estimate minimally important differences for four preference-based health-related quality of life instruments. Medical Care, 48, 365–371

    Article  PubMed  Google Scholar 

  61. Lee, B. B., King, M. T., Simpson, J. M., Haran, M. J., Stockler, M. R., Marial, O., et al. (2008). Validity, responsiveness, and minimal important difference for the SF-6D health utility scale in a spinal cord injured population. Value in Health, 11(4), 680–688

    Article  PubMed  Google Scholar 

  62. Norman, R., Church, J., van den Berg, B., & Goodall, S. (2013). Australian health-related quality of life population norms derived from the SF-6D. Australian and New Zealand Journal of Public Health, 37(1), 17–23

    Article  PubMed  Google Scholar 

  63. Van den Berg, B. (2012). SF-6D population norms. Health Economics, 21(12), 1508–1512

    Article  PubMed  Google Scholar 

  64. Antony, B., Venn, A., Cicuttini, F., March, L., Blizzard, L., Dwyer, T., et al. (2015). Association of physical activity and physical performance with tibial cartilage volume and bone area in young adults. Arthritis Research & Therapy. https://doi.org/10.1186/s13075-015-0813-0

    Article  Google Scholar 

  65. Agaliotis, M., Fransen, M., Bridgett, L., Nairn, L., Votrubec, M., Jan, S., et al. (2013). Risk factors associated with reduced work productivity among people with chronic knee pain. Osteoarthritis and Cartilage, 21(9), 1160–1169

    Article  CAS  PubMed  Google Scholar 

  66. Sayre, E. C., Li, L. C., Kopec, J. A., Esdaile, J. M., Bar, S., & Cibere, J. (2010). The effect of disease site (knee, hip, hand, foot, lower back or neck) on employment reduction due to osteoarthritis. PLoS ONE, 5(5), e10470

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  67. Hubertsson, J., Petersson, I. F., Thorstensson, C. A., & Englund, M. (2013). Risk of sick leave and disability pension in working-age women and men with knee osteoarthritis. Annals of the Rheumatic Diseases, 72(3), 401–405

    Article  PubMed  Google Scholar 

  68. Afzali, T., Fangel, M. V., Vestergaard, A. S., Rathleff, M. S., Ehlers, L. H., & Jensen, M. B. (2018). Cost-effectiveness of treatments for non-osteoarthritic knee pain conditions: A systematic review. PLoS ONE, 13(12), e0209240

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Ara, R., Brazier, J., & Zouraq, I. A. (2017). The use of health state utility values in decision models. PharmacoEconomics, 35(1), 77–88

    Article  PubMed  Google Scholar 

  70. Ara, R., & Brazier, J. E. (2010). Populating an economic model with health state utility values: Moving toward better practice. Value in Health, 13(5), 509–518

    Article  PubMed  Google Scholar 

  71. Ara, R., & Wailoo, A. (2012). Using health state utility values in models exploring the cost-effectiveness of health technologies. Value in Health, 15(6), 971–974

    Article  PubMed  Google Scholar 

  72. Paxton, E. S., Kymes, S. M., & Brophy, R. H. (2010). Cost-effectiveness of anterior cruciate ligament reconstruction: A preliminary comparison of single-bundle and double-bundle techniques. The American Journal of Sports Medicine, 38(12), 2417–2425

    Article  PubMed  Google Scholar 

  73. Brazier, J. (2008). Valuing health states for use in cost-effectiveness analysis. PharmacoEconomics, 26(9), 769–779

    Article  PubMed  Google Scholar 

  74. Wilson, R., & Abbott, J. H. (2018). Development and validation of a new population-based simulation model of osteoarthritis in New Zealand. Osteoarthritis Cartilage, 26(4), 531–539

    Article  CAS  PubMed  Google Scholar 

  75. Abbott, J. H., Usiskin, I. M., Wilson, R., Hansen, P., & Losina, E. (2017). The quality-of-life burden of knee osteoarthritis in New Zealand adults: A model-based evaluation. PLoS ONE, 12(10), e0185676

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  76. Muraki, S., Akune, T., Oka, H., En-Yo, Y., Yoshida, M., Saika, A., et al. (2011). Health-related quality of life in subjects with low back pain and knee pain in a population-based cohort study of Japanese men: The Research on Osteoarthritis Against Disability study. Spine (Phila Pa 1976), 36(16), 1312–1319

    Article  Google Scholar 

  77. Antonopoulou, M. D., Alegakis, A. K., Hadjipavlou, A. G., & Lionis, C. D. (2009). Studying the association between musculoskeletal disorders, quality of life and mental health. A primary care pilot study in rural Crete, Greece. BMC Musculoskeletal Disorders, 10, 143

    Article  PubMed  PubMed Central  Google Scholar 

  78. Norimatsu, T., Osaki, M., Tomita, M., Ye, Z., Abe, Y., Honda, S., et al. (2011). Factors predicting health-related quality of life in knee osteoarthritis among community-dwelling women in Japan: The Hizen-Oshima study. Orthopedics, 34(9), e535–e540

    Article  PubMed  Google Scholar 

  79. Hoogeboom, T. J., den Broeder, A. A., de Bie, R. A., & van den Ende, C. H. M. (2013). Longitudinal impact of joint pain comorbidity on quality of life and activity levels in knee osteoarthritis: Data from the Osteoarthritis Initiative. Rheumatology (Oxford, England), 52(3), 543–546

    Article  Google Scholar 

  80. Kauppila, A. M., Kyllonen, E., Mikkonen, P., Ohtonen, P., Laine, V., Siira, P., et al. (2009). Disability in end-stage knee osteoarthritis. Disability and Rehabilitation, 31(5), 370–380

    Article  PubMed  Google Scholar 

  81. Adegoke, B. O., Babatunde, F. O., & Oyeyemi, A. L. (2012). Pain, balance, self-reported function and physical function in individuals with knee osteoarthritis. Physiotherapy Theory and Practice, 28(1), 32–40

    Article  PubMed  Google Scholar 

  82. Jordan, J., Luta, G., Renner, J., Dragomir, A., Hochberg, M., & Fryer, J. (1997). Knee pain and knee osteoarthritis severity in self-reported task specific disability: The Johnston County Osteoarthritis Project. Journal of Rheumatology, 24(7), 1344–1349

    CAS  Google Scholar 

  83. Cherepanov, D., Palta, M., Fryback, D. G., & Robert, S. A. (2010). Gender differences in health-related quality-of-life are partly explained by sociodemographic and socioeconomic variation between adult men and women in the US: Evidence from four US nationally representative data sets. Quality of Life Research, 19(8), 1115–1124

    Article  PubMed  PubMed Central  Google Scholar 

  84. Lundberg, L., Johannesson, M., Isacson, D. G. L., & Borgquist, L. (1999). Health-state utilities in a general population in relation to age, gender and socioeconomic factors. European Journal of Public Health, 9(3), 211–217

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge the contributions of the CDAH project manager, Marita Dalton, CDAH participants, funders, and all other project staff.

Funding

AS is supported by the International Graduate Research Scholarship, University of Tasmania. BA is supported by the National Health and Medical Research Council of Australia Fellowship. The CDAH study was supported by the National Health and Medical Research Council Project Grant 211316. CDAH-knee sub-study was supported by the Royal Hobart Hospital Research Foundation (RHHRF) Grant 18-202 RHHRF.

Author information

Authors and Affiliations

Authors

Contributions

AS, BA, and AP conceived the Study. AS, JC, and LB conceived the present analysis. AS and LB cleaned and prepared the data and performed the analysis. AS and JC undertook HSU estimation using the algorithm. AS drafted the first draft of the manuscript, and JC, AV, GJ, LB, AP TD, FC, CD, and BA edited the manuscript. All authors commented on and approved the final version of the manuscript.

Corresponding author

Correspondence to Benny Antony.

Ethics declarations

Conflict of interest

All authors declare that there is no conflict of interest.

Ethical approval

The Southern Tasmania Health and Medical Human Research Ethics Committee, Monash University Human Research Ethics Committee, and the Northern Sydney and Central Coast Area Human Research Ethics Committee provided ethical approval for the study (Ethics ID: H0018491).

Informed consent

Participants were asked to read the participant information and to consent before entering the study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 61 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singh, A., Campbell, J.A., Venn, A. et al. Association between knee symptoms, change in knee symptoms over 6–9 years, and SF-6D health state utility among middle-aged Australians. Qual Life Res 30, 2601–2613 (2021). https://doi.org/10.1007/s11136-021-02859-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-021-02859-5

Keywords

Navigation