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Published online January 9, 2008
Diabetes Care 31:795-797, 2008
DOI: 10.2337/dc07-1391
© 2008 by the American Diabetes Association
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Cardiovascular and Metabolic Risk
Original Research

Can Self-Rated Health Scores Be Used for Risk Prediction in Patients With Type 2 Diabetes?

Alison J. Hayes, PHD1, Philip M. Clarke, PHD1, Paul G. Glasziou, PHD2, R. John Simes, FRACP3, Paul L. Drury, FRACP4 and Anthony C. Keech, FRACP3

1 School of Public Health, University of Sydney, Sydney, New South Wales, Australia
2 Department of Primary Care, University of Oxford, Oxford, U.K
3 National Health & Medical Research Council Clinical Trials Centre, University of Sydney, Sydney, New South Wales, Australia
4 Auckland Diabetes Centre, Auckland, New Zealand

Address correspondence and reprint requests to Dr. Alison Hayes, School of Public Health, University of Sydney, NSW 2006 Australia. E-mail: alisonh{at}health.usyd.edu.au


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESEARCH DESIGN AND METHODS--
 RESULTS--
 CONCLUSIONS--
 References
 
OBJECTIVE—To investigate whether self-rated health profiles compiled using the EuroQol group’s visual analog scale (EQ VAS) are independent predictors of vascular events and major complications in people with type 2 diabetes after controlling for standard clinical risk factors.

RESEARCH DESIGN AND METHODS—The study is based on 7,348 individuals with a mean follow-up of 2.4 years after completing the EQ-5D questionnaire. We used Cox proportional hazards modeling to estimate hazard ratios associated with EQ VAS scores after controlling for baseline covariates: age, sex, smoking status, diabetes duration, A1C, systolic blood pressure, BMI, plasma lipids, and prior clinical history.

RESULTS—A 10-point higher EQ VAS score was associated with a 6% (95% CI 1–11) lower risk of vascular events and a 22% (95% CI 15–28) lower risk of diabetesc complications.

CONCLUSIONS—Self-rated health profiles compiled using the EQ VAS provide valuable information on patient risk in addition to that determined from clinical risk factors alone.

Abbreviations: VAS, visual analog scale • FIELD, Finofibrate Intervention and Event Lowering in Diabetes study


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESEARCH DESIGN AND METHODS--
 RESULTS--
 CONCLUSIONS--
 References
 
Several risk models are available for people with diabetes (1–3) based on clinical risk factors such as systolic blood pressure and A1C. These provide a means of identifying high-risk patients to target the management of diabetes care (4) and can be used for economic evaluation of diabetes therapies (5). To date, little attention has been given to the role of subjective measures of health in risk assessment; few studies have considered outcomes other than mortality that are particularly relevant to people with diabetes, whose risk of cardiovascular and other complications is elevated (6).

Studies on self-rated health have consistently shown that people who report their health status as "poor" or "fair" have higher mortality than those reporting their health as "excellent" or "good" (7). Self-rated health may also be measured with a visual analog scale (VAS), e.g., the EuroQol (EQ) VAS from the EQ-5D (8), a thermometer-like scale with zero representing the worst and 100 the best imaginable health state. In this study, we examined whether self-rated health measured by the EQ VAS is an independent predictor of cardiovascular events and major diabetes complications in individuals with type 2 diabetes.


   RESEARCH DESIGN AND METHODS—
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS--
RESULTS--
 CONCLUSIONS--
 References
 
The study is based on Australian and New Zealand participants of the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study (9) who participated in a quality-of-life substudy. We focused on two end points: cardiovascular events and other diabetes-related complications (see Table 1 and the online appendix, which is available at http://dx.doi.org/10.2337/dc07-1391).


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  		Table 1— Cox proportional hazard ratios (HRs) for fatal and nonfatal vascular events and complications of diabetes

 
Baseline values of clinical risk factors were calculated as an average of all available measures between trial randomization and first administration of the EQ-5D questionnaire. Mean values from the whole sample were imputed for patients (<1% of the sample) with any missing baseline risk factors.

Log-rank methods without adjustment for covariates were used to test for significant differences in risk among patients categorized into approximate quartiles according to their EQ VAS scores.

We used Cox proportional hazards modeling to estimate hazard ratios (HRs) associated with EQ VAS scores after controlling for baseline covariates of age, sex, smoking status, diabetes duration, A1C, systolic blood pressure, BMI, plasma lipids, and prior clinical history. We investigated any heterogeneity in the HR of the VAS by an interaction term with prior events. Risk factors were dropped from the models through stepwise elimination if their HRs were not significantly different from 1.0 (P > 0.1). The proportional hazards assumption was tested using Schoenfeld residuals (10). Stata/SE (version 9.1; Stata, College Station, TX) was used for all statistical analyses.


   RESULTS—
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS--
 RESULTS--
CONCLUSIONS--
 References
 
A total of 7,348 patients (87.5% of all Australian and New Zealand patients in the FIELD trial) consented and correctly answered a written EQ-5D questionnaire at an average of 2.9 years after trial randomization, generating a mean follow-up of 2.4 years. Mean ± SD patient age was 66 ± 6.9 years; 91.8% were white and 38% women. Mean EQ VAS score was 77.8 ± 15.9; other baseline risk factors were similar to those reported in the FIELD trial (11). The cumulative hazard of vascular events and complications was stratified by patients’ baseline EQ VAS score (P < 0.001), with differences most pronounced for patients scoring below 70 (see online appendix).

After adjustment for other risk factors, EQ VAS scores remained significant independent predictors of cardiovascular events, with a 10-point increase in EQ VAS score associated with a 6% (95% CI 1–11) decrease in risk of a future event (Table 1). Patients with a history of any prior event were three times more likely to experience a vascular event.

A 10-point change in EQ VAS score was associated with a 22% (95% CI 15–28) reduction in the risk of complications for patients with no known clinical history of any events. For individuals with a history of prior events, the EQ VAS score was not significantly associated with future complications (P = 0.054).


   CONCLUSIONS—
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS--
 RESULTS--
 CONCLUSIONS--
References
 
This study demonstrates that self-rated health reported on the EQ VAS provides additional valuable information on the risk of vascular events and complications in individuals with type 2 diabetes over and above that determined from clinical history and established risk factors alone.

Possible reasons for patients with lower self-rated health profiles having poorer outcomes are that self-rated health profiles are markers of disease severity or could indicate diabetes-related complications at a subclinical stage. Interestingly, the increase in relative risk associated with the EQ VAS is less for acute events such as mydocardial infarction than for more chronic complications.

Self-rated health has received little attention in the literature on risk assessment for diabetes and was not listed in a recent editorial of emerging risk factors for cardiovascular disease (12) or in a statement on risk factors for cardiovascular disease in diabetes (13). One recent study indicated that measures of social functioning were significant predictors of mortality and disability in people with diabetes (14), and the Wisconsin Epidemiologic Study of Diabetic Retinopathy showed that health-related quality of life can predict mortality in people with type 2 diabetes (15). Our study extends these findings by demonstrating that self-reported health profiles can predict which patients are at higher risk for major complications of diabetes even after taking into account established risk factors.

The EQ VAS could potentially be used in a clinical setting to target primary prevention in diabetes patients. Our results suggest that a 10-point difference in EQ VAS score stratifies risk of complications to a greater degree than either a 1-unit change in the ratio of total cholesterol to HDL cholesterol or a 10-year longer duration of diabetes. A key feature of the VAS in this setting is its simplicity: it only requires patients to indicate a score on a 0 to 100-point scale to represent their current health status.

The models presented here focus on a single measure of self-rated health and demonstrate how variations in this measure across a population affect subsequent outcomes. Whether change in health status at an individual level can also predict risk is unknown. Addressing this question would require repeated measures of EQ VAS on the same individual.


   Acknowledgments
 
A detailed list of acknowledgments can be found in the online appendix.


   Footnotes
 
Published ahead of print at http://care.diabetesjournals.org on 9 January 2008. DOI: 10.2337/dc07-1391.

Additional information for this article can be found in an online appendix at http://dx.doi.org/10.2337/dc07-1391.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C Section 1734 solely to indicate this fact.

Received for publication July 19, 2007. Accepted for publication December 27, 2007.


   References
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS--
 RESULTS--
 CONCLUSIONS--
 References
 

  1. Stevens RJ, Kothari V, Adler AI, Stratton IM: The UKPDS risk engine: a model for the risk of coronary heart disease in type II diabetes (UKPDS 56) Clin Sci 101:671–679, 2001[Medline]
  2. Kothari V, Stevens RJ, Adler AI, Stratton IM, Manley SE, Neil HA, Holman RR: UKPDS 60: risk of stroke in type 2 diabetes estimated by the UK Prospective Diabetes Study risk engine. Stroke 33:1776–1781, 2002[Abstract/Free Full Text]
  3. Clarke PM, Gray AM, Briggs A, Farmer AJ, Fenn P, Stevens RJ, Matthews DR, Stratton IM, Holman RR, the UK Prospective Diabetes Study Group: A model to estimate the lifetime health outcomes of patients with type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS no. 68). Diabetologia 47:1747–1759, 2004[Medline]
  4. Song SH, Brown PM: Coronary heart disease risk assessment in diabetes mellitus: comparison of UKPDS risk engine with Framingham risk assessment function and its clinical implications. Diabet Med 21:238–245, 2004[Medline]
  5. Clarke PM, Gray AM, Briggs A, Stevens RJ, Matthews DR, Holman R; UKPDS 72 United Kingdom Prospective Diabetes Study: Cost utility analyses of intensive blood glucose and tight blood pressure control in type 2 diabetes (UKPDS 72). Diabetologia 48:868–877, 2005[Medline]
  6. Haffner SM: Coronary heart disease in patients with diabetes. N Engl J Med 342:1040–1042, 2000[Free Full Text]
  7. Idler EL, Benyamini Y: Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav 38:21–37, 1997[Medline]
  8. Rabin R, de Charro F: EQ-5D: a measure of health status from the EuroQol Group. Ann Med 33:337–343, 2001[Medline]
  9. FIELD Study Investigators: The need for a large-scale trial of fibrate therapy in diabetes: the rationale and design of the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study. [ISRCTN64783481]. Cardiovasc Diabetol 3:9, 2004[Medline]
  10. Schoenfeld D: Partial residuals for the proportional hazards regression model. Biometrika 69:239–241, 1982[Abstract/Free Full Text]
  11. Keech A, Simes RJ, Barter P, Best J, Scott R, Taskinen MR, Forder P, Pillai A, Davis T, Glasziou P, Drury P, Kesäniemi YA, Sullivan D, Hunt D, Colman P, d’Emden M, Whiting M, Ehnholm C, Laakso M, the FIELD Study Investigators: Effects of long term Fenofibrate therapy on cardiovascular events in 9795 people with type 2 diabetes mellitus (the FIELD study): randomized controlled trial. Lancet 366:1849–1861, 2005[Medline]
  12. Cobb FR, Kraus WE, Root M, Allen JD: Assessing risk for coronary heart disease: beyond Framingham. Am Heart J 146:572–580, 2003[Medline]
  13. Grundy SM, Benjamin IJ, Burke GL, Chait A, Eckel RH, Howard BV, Mitch W, Smith SC Jr, Sowers JR: Diabetes and cardiovascular disease: a statement for healthcare professionals from the American Heart Association. Circulation 100:1134–1146, 1999[Free Full Text]
  14. Kuo Y-F, Raji MA, Peek MK, Goodwin JS: Health-related social disengagement in elderly diabetic patients: association with subsequent diability and survival. Diabetes Care 27:1630–1637, 2004[Abstract/Free Full Text]
  15. Dasbach EJ, Klein R, Klein BE, Moss SE: Self-rated health and mortality in people with diabetes. Am J Public Health 84:1775–1779, 1994[Abstract/Free Full Text]

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This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Online-Only Appendix
Right arrow All Versions of this Article:
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Right arrow Articles by Hayes, A. J.
Right arrow Articles by Keech, A. C.
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HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
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