Skip to main content

Advertisement

SpringerLink
Log in

How do clinical and psychological variables relate to quality of life in end-stage renal disease? Validating a proximal–distal model

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

Abstract

Purpose

The aims of this study were to: (1) validate the proximal–distal (PD) model in predialysis and early dialysis and (2) examine the role of hemoglobin on quality of life (QoL) in these patient groups.

Methods

Cross-sectional observational studies of 475 participants recruited from four major university teaching hospitals were conducted. The multi-sample structural equation modeling with latent composite techniques was employed to test the PD model. Seven factors were measured, including QoL, positive affect, depression, physical functioning, kidney disease symptoms, comorbidity and hemoglobin.

Results

The results showed that both the equality-constrained and equality-unconstrained PD models were supported by fit statistics. The chi square difference test of the two models was non-significant, indicating that the PD model was consistent across groups. The alternative models were rejected by fit statistics, suggesting that hemoglobin does not impact on psychological states but QoL.

Conclusions

This study validates the PD model across the end-stage renal disease (ESRD) patient groups and shows a hierarchical causal relationship between clinical factors, physical functioning, psychological states and QoL, with hemoglobin as an exception. This model provides an empirical framework for integrating and studying a range of clinical factors and health outcomes in ESRD.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Abbreviations

ESRD:

End-stage renal disease

QoL:

Quality of life

PD:

Proximal–distal

eGFR:

Estimated glomerular filtration rate

IQoL:

Individual quality of life

PA:

Positive affect

SEIQoL-DW:

The schedule for evaluation of individual quality-of-life direct weighting

DASS21:

Depression anxiety stress scale 21

PAS:

Positive affect scale

CMI:

Comorbidity index

KDSS:

Kidney disease symptom status

SLS:

Symptoms list scale

KDQoL-SF™:

Kidney disease quality of life short form

PCS:

Physical component scale

SEM:

Structural equation modeling

MSEM:

Multi-sample structural equation modeling

LC:

Latent composite

GFI:

Goodness-of-fit index

AGFI:

Adjusted goodness-of-fit index

SRMR:

Standardized root mean square residual

RMSEA:

Root mean square error of approximation

NNFI:

Non-normed fit index

CFI:

Comparative fit index

References

  1. Wilson, I. B., & Cleary, P. D. (1995). Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. Journal of American Medical Association, 273(1), 59–65.

    Article  CAS  Google Scholar 

  2. Kaptein, A. A., van Dijk, S., Broadbent, E., Falzon, L., Thong, M., & Dekker, F. W. (2010). Behavioural research in patients with end-stage renal disease: A review and research agenda. Patient Education and Counselling, 81(1), 23–29.

    Article  Google Scholar 

  3. Finkelstein, F. O., Wuerth, D., & Finkelstein, S. H. (2009). Health related quality of life and the CKD patient: Challenges for the nephrology community. Kidney International, 76(9), 946–952.

    Article  PubMed  Google Scholar 

  4. Brenner, M. H., Curbow, B., & Legro, M. W. (1995). The proximal-distal continuum of multiple health outcome measures: The case of cataract surgery. Medical Care, 34(4), AS236–AS244.

    Google Scholar 

  5. Baker, S. R., Pearson, N. K., & Robinson, P. G. (2008). Testing the applicability of a conceptual model of oral health in housebound edentulous older people. Community Dentistry and Oral Epidemiology, 36(3), 237–248.

    Article  PubMed  Google Scholar 

  6. Hofer, S., Benzer, W., Alber, H., Ruttmann, E., Kopp, M., Schussler, G., et al. (2005). Determinants of health-related quality of life in coronary artery disease patients: A prospective study generating a structural equation model. Psychosomatics, 46(3), 212–223.

    Article  PubMed  Google Scholar 

  7. Sousa, K. H., & Kwok, O. M. (2006). Putting Wilson and Cleary to the test: Analysis of a HRQOL conceptual model using structural equation modeling. Quality of Life Research, 15(4), 725–737.

    Article  PubMed  Google Scholar 

  8. Sullivan, M. D., Kempen, G. I. J. M., Sonderen, E. V., & Ormel, J. (2000). Models of health-related quality of life in a population of community-dwelling Dutch elderly. Quality of Life Research, 9(7), 801–810.

    Article  PubMed  CAS  Google Scholar 

  9. Chan, R., Brooks, R., Erlich, J., Gallagher, M., Snelling, P., Chow, J., et al. (2011). Studying psychosocial adaptation to end-stage renal disease: The proximal-distal model of health-related outcomes as a base model. Journal of Psychosomatic Research, 70(5), 455–464.

    Article  PubMed  Google Scholar 

  10. Baker, S. R., Pankhurst, C. L., & Robinson, P. G. (2007). Testing relationships between clinical and non-clinical variables in xerostomia: A structural equation model of oral health-related quality of life. Quality of Life Research, 16(2), 297–308.

    Article  PubMed  Google Scholar 

  11. McKenna, S. P., & Doward, L. C. (2004). Integrating patient-reported outcomes. Value in Health, 7, 9–12.

    Article  Google Scholar 

  12. Kring, D., & Crane, P. (2009). Factors affecting quality of life in persons on hemodialysis. Nephrology Nursing Journal, 36(1), 15–24.

    PubMed  Google Scholar 

  13. Chan, R., Steel, Z., Brooks, R., Heung, T., Erlich, J., Chow, J., & Suranyi, M. (2011). The psychosocial correlates of quality of life in the dialysis population: A systematic review and meta-regression analysis. Submitted to quality of life research.

  14. Chan, R., Brooks, R., Gallagher, M., Erlich, J., Snelling, P., Chow, J., et al. (2010). Measuring kidney-disease-related loss in the samples of pre-dialysis and dialysis patients: Validating the kidney disease loss scale. Clinical Journal of The American Society of Nephrology: CJASN, 5, 1249–1254.

    Article  PubMed Central  PubMed  Google Scholar 

  15. O’Boyle, C. A., McGee, H. M., Hickey, A., Joyce, C. R. B., Browne, J., O’Malley, K., et al. (1993). The schedule for the evaluation of individual quality of life (SEIQoL): A direct weighting procedure for quality of life domains (SEIQoL-DW) administration manual. Dublin: Department of Psychology, Royal College of Surgeons in Ireland.

    Google Scholar 

  16. Hickey, A. M., Bury, G., O’Boyle, C. A., Bradley, F., O’Kelly, F. D., & Shannon, W. (1996). A new short form individual quality of life measure (SEIQoL-DW): Application in a cohort of individuals with HIV/AIDS. British Medical Journal, 313(7048), 29–33.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  17. Joyce, C. R. B., Hickey, A., McGee, H. M., & O’Boyle, C. A. (2003). A theory-based method for the evaluation of individual quality of life: The SEIQoL. Quality of Life Research, 12(3), 275–280.

    Article  PubMed  CAS  Google Scholar 

  18. Tovbin, D., Gidron, Y., Jean, T., Granovsky, R., & Schnieder, A. (2003). Relative importance and interrelations between psychosocial factors and individualized quality of life of hemodialysis patients. Quality of Life Research, 12(6), 709–717.

    Article  PubMed  Google Scholar 

  19. Kimmel, P. L., & Peterson, R. A. (2005). Depression in end-stage renal disease patients treated with hemodialysis: Tools, correlates, outcomes, and needs. Seminars in Dialysis, 18(2), 91–97.

    Article  PubMed  Google Scholar 

  20. Lovibond, P. F., & Lovibond, S. H. (1995). The structure of negative emotional states: Comparison of the depression anxiety stress scales (DASS) with the beck depression and anxiety inventories. Behaviour Research and Therapy, 33(3), 335–343.

    Article  PubMed  CAS  Google Scholar 

  21. Antony, M. M., Bieling, P. J., Cox, B. J., Enns, M. W., & Swinson, R. P. (1998). Psychometric properties of the 42-item and 21-item versions of the depression anxiety stress scales in clinical groups and a community sample. Psychological Assessment, 10(2), 176–181.

    Article  Google Scholar 

  22. Clara, I. P., Cox, B. J., & Enns, M. W. (2001). Confirmatory factor analysis of the depression-anxiety-stress scales in depressed and anxious patients. Journal of Psychopathology and Behavioral Assessment, 23(1), 61–67.

    Article  Google Scholar 

  23. Henry, J. D., & Crawford, J. R. (2005). The short-form version of the depression anxiety stress scales (DASS-21): Construct validity and normative data in a large non-clinical sample. British Journal of Clinical Psychology, 44(2), 227–239.

    Article  PubMed  Google Scholar 

  24. Ng, F., Trauer, T., Dodd, S., Callaly, T., Campbell, S., & Berk, M. (2007). The validity of the 21-item version of the depression anxiety stress scales as a routine clinical outcome measure. Acta Neuropsychiatrica, 19(5), 304–310.

    Article  Google Scholar 

  25. Brooks, R. (1999). Health related quality of life of intensive care patients : Development of the Sydney quality of life questionnaire. Sydney: UNSW.

    Google Scholar 

  26. Chan, R., Brooks, R., Erlich, J., Chow, J., & Suranyi, M. (2009). The effects of kidney-disease-related loss on long-term dialysis patients’ depression and quality of life: Positive affect as a mediator. Clinical Journal of The American Society of Nephrology: CJASN, 4(1), 160–167.

    Article  PubMed Central  PubMed  Google Scholar 

  27. Friedman, E. A. (1991). Diabetic nephropathy. In W. N. Suki & S. G. Massry (Eds.), Thearpy of renal diseases and related disorders (2nd ed., pp. 533–542). Boston: Kluwer Academic Publishers.

    Chapter  Google Scholar 

  28. Charlson, M. E., Pompei, P., Ales, K. L., & MacKenzie, C. R. (1987). A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Diseases, 40(5), 373–383.

    Article  PubMed  CAS  Google Scholar 

  29. Hays, R. D., Kallich, J. D., Mapes, D. L., Coons, S. J., Amin, N., Carter, W. B., & Kamberg, C. (1997). Kidney disease quality of life short form (KDQOL-SF), version 1.3: A manual for use and scoring. Santa Monica, CA: RAND, P-7928.

  30. Ware, J. E., Jr, Kosinski, M., Turner-Bowker, D. M., & Gandek, B. (2002). How to score version 2 of the SF-12 @ health survey (with a supplement documenting version 1). Lincoln: QualityMetric Incorporated.

    Google Scholar 

  31. SPSS for Windows. (2009). PASW statistics 18. Chicago: SPSS Inc.

    Google Scholar 

  32. Jöreskog, K. G., & Sorbom, D. (2004). LISREL 8.72: User’s reference guide. Chicago: Scientific Software International.

  33. Landis, R. S., Beal, D. J., & Tesluk, P. E. (2000). A comparison of approaches to forming composite measures in structural equation models. Organizational Research Methods, 3(2), 186–206.

    Article  Google Scholar 

  34. Grace, J. B., & Bollen, K. A. (2008). Representing general theoretical concepts in structural equation models: The role of composite variables. Environmental and Ecological Statistics, 15(2), 191–213.

    Article  Google Scholar 

  35. Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.

    Google Scholar 

  36. Stephenson, M. T., & Holbert, R. L. (2003). A Monte Carlo simulation of observable versus latent variable structural equation modeling techniques. Communication Research, 30(3), 332–354.

    Article  Google Scholar 

  37. Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). New York: The Guilford Press.

    Google Scholar 

  38. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.

    Article  Google Scholar 

  39. Hoyle, R. H., & Smith, G. T. (1994). Formulating clinical research hypotheses as structural equation models: A conceptual overview. Journal of Consulting and Clinical Psychology, 62(3), 429–440.

    Article  PubMed  CAS  Google Scholar 

  40. McDonald, R. P. (1997). Haldane’s lungs: A case study in path analysis. Multivariate Behavioral Research, 32(1), 1–38.

    Article  Google Scholar 

  41. MacKinnon, D. (2008). Introduction to statistical mediation analysis. NY: Routledge Academic.

    Google Scholar 

  42. Reise, S. P., Widaman, K. F., & Pugh, R. H. (1993). Confirmatory factor analysis and item response theory: Two approaches for exploring measurement invariance. Psychological Bulletin, 114(3), 552–566.

    Article  PubMed  CAS  Google Scholar 

  43. Chou, C.-P., & Bentler, P. M. (1995). Estimates and tests in structural equation modeling. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 37–55). Thousand Oaks: Sage Publications, Inc.

    Google Scholar 

  44. Chou, C.-p., Bentler, P. M., & Satorra, A. (1991). Scaled test statistics and robust standard errors for non-normal data in covariance structure analysis: A Monte Carlo study. British Journal of Mathematical and Statistical Psychology, 44(2), 347–357.

    Article  PubMed  Google Scholar 

  45. Satorra, A., & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variable analysis: Applications for developmental research (pp. 399–419). Thousand Oaks: Sage.

    Google Scholar 

  46. Spiegel, B. M., Melmed, G., Robbins, S., Esrailian, E., Spiegel, B. M. R., Melmed, G., et al. (2008). Biomarkers and health-related quality of life in end-stage renal disease: A systematic review. Clinical Journal of The American Society of Nephrology: CJASN, 3(6), 1759–1768.

    Article  PubMed Central  PubMed  Google Scholar 

  47. Chan, R., Brooks, R., Steel, Z., Heung, T., Erlich, J., Chow, J., et al. (2012). The psychosocial correlates of quality of life in the dialysis population: A systematic review and meta-regression analysis. Quality of Life Research, 21, 563–580.

    Article  PubMed  Google Scholar 

  48. Kaplan, S. H., Kravitz, R. L., & Greenfield, S. (2000). A critique of current uses of health status for the assessment of treatment effectiveness and quality of care. Medical Care, 38(9 Suppl), 184–191.

    Google Scholar 

  49. Bishop, M. (2007). Quality of life and psychosocial adaptation to chronic illness and acquired disability: A conceptual and theoretical synthesis. In A. E. Dell Orto & P. W. Power (Eds.), The psychological and social impact of illness and disability (5th ed., pp. 230–248). New York: Springer Publishing Co.

    Google Scholar 

  50. Gatchel, R. J., Peng, Y. B., Peters, M. L., Fuchs, P. N., & Turk, D. C. (2007). The biopsychosocial approach to chronic pain: Scientific advances and future directions. Psychological Bulletin, 133(4), 581–624.

    Article  PubMed  Google Scholar 

  51. Engel, G. L. (1977). The need for a new medical model: A challenge for biomedicine. Science, 196, 129–136.

    Article  PubMed  CAS  Google Scholar 

  52. Pearl, J. (2000). Causality: Models, reasoning, and inference. Cambridge: Cambridge University Press.

    Google Scholar 

  53. Lei, P. W., & Wu, Q. (2007). Introduction to structural equation modeling: Issues and practical considerations. Educational Measurement: Issues and Practice, 26(3), 33–43.

    Article  Google Scholar 

Download references

Acknowledgments

The results of this paper were presented at the 46th Annual Scientific Meeting of the Australian and New Zealand Society of Nephrology, Perth, Australia, 2010. The abstract of this paper has been published in Nephrology (Chan, R., Brooks, R., Erlich, J., Gallagher, M., Snelling, P., Chow, J., and Suranyi, M.: Integrating clinical variables, health outcomes, and quality of life in ESRD: The PD model of health-related outcomes, [Abstract], Nephrology 15 (S4), 75, 2010). We wish to thank all staff and patients in participating hospitals for their support and assistance.

Author information

Authors and Affiliations

  1. Consultation Liaison Psychiatry, Liverpool Hospital, Locked Bag 7103, Liverpool, BC, NSW, 1871, Australia

    Ramony Chan

  2. Renal Unit, Liverpool Hospital, Sydney, Australia

    Ramony Chan, Josephine Chow & Michael Suranyi

  3. The University of New South Wales, Sydney, Australia

    Ramony Chan, Jonathan Erlich & Michael Suranyi

  4. Healing Foundation, Canberra, Australia

    Robert Brooks

  5. Department of Nephrology, Prince of Wales Hospital, Sydney, Australia

    Jonathan Erlich

  6. Department of Renal Medicine, Concord Repatriation and General Hospital, Sydney, Australia

    Martin Gallagher

  7. Department of Renal Medicine, Royal Prince Alfred Hospital, Sydney, Australia

    Paul Snelling

  8. The University of Sydney, Sydney, Australia

    Josephine Chow

  9. The University of Tasmania, Hobart, Australia

    Josephine Chow

Authors
  1. Ramony Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Robert Brooks
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jonathan Erlich
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Martin Gallagher
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Paul Snelling
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Josephine Chow
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Michael Suranyi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ramony Chan.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chan, R., Brooks, R., Erlich, J. et al. How do clinical and psychological variables relate to quality of life in end-stage renal disease? Validating a proximal–distal model. Qual Life Res 23, 677–686 (2014). https://doi.org/10.1007/s11136-013-0499-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-013-0499-1

Keywords

Search

Navigation