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Keywords:

  • Generic health status;
  • Quality of life;
  • Fibromyalgia;
  • Rheumatoid arthritis;
  • Osteoarthritis

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Objective

To assess the performance of a generic health-related quality of life (HRQOL) measure in a rheumatology clinic population.

Methods

Participants (n = 619) with fibromyalgia, rheumatoid arthritis, or osteoarthritis receiving care from rheumatologists completed mailed questionnaires that included the Behavioral Risk Factor Surveillance System (BRFSS) HRQOL measure and condition-specific measures assessing disability, pain, fatigue, and helplessness. The BRFSS assesses global health and number of days in the past 30 of poor physical or mental health or activity limitation. The overall sample was described, followed by comparison of adjusted scores on all HRQOL measures by diagnosis.

Results

Participants reported mild difficulty with activities of daily living, marked pain and fatigue, and moderate helplessness. Participants reported a mean of 8 or more days out of 30 of poor physical and mental health and activity limitations; more than 40% reported poor or fair health. Participants with fibromyalgia reported more ill health on condition-specific measures and the BRFSS HRQOL measures than did participants with osteoarthritis or rheumatoid arthritis.

Conclusion

The BRFSS HRQOL measure is a brief, easily administered, generic health indicator that shows differences among rheumatic disease diagnoses.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Quality of life is a broad, subjective construct that encompasses multiple levels and that varies with cultural context (1). Consideration of health-related quality of life (HRQOL) has become increasingly important in decisions regarding resource allocation, intervention design, and treatment of individuals with chronic disease (2–12). HRQOL is most often recognized as an individual's perception of his or her own health that can clearly and directly affect physical or mental health (1, 13, 14). Thus, HRQOL is predictive of morbidity and mortality (15–19). Although not intended to provide a detailed picture of specific conditions or populations, generic HRQOL measures do allow for general comparisons across different health conditions. Several measures have been used as generic HRQOL indicators, including the EuroQol (20), Quality of Well-Being Scale (21, 22), Nottingham Health Profile (23, 24), Sickness Impact Profile (25, 26), and Medical Outcomes Study Short Form 36 (SF-36) (27, 28).

In 1993, the National Center for Chronic Disease Prevention and Health Promotion at the Centers for Disease Control and Prevention developed a set of 4 “healthy days” items, to measure generic HRQOL in the general population for the Behavioral Risk Factor Surveillance System (BRFSS) core survey. The healthy days items assess self- rated global health and the number of days in the past 30 of poor physical or mental health or limitations in usual activities (29, 30). Intended as a surveillance tool for public health, the BRFSS healthy days items were designed to be easily administered and understandable to the general public and to represent HRQOL on a personal level (29, 30). The National Arthritis Action Plan proposes using the BRFSS healthy days measures and arthritis questions for the surveillance of arthritis prevalence and impact within the population (31, 32).

In a statewide study of a representative sample of Missouri residents, the BRFSS HRQOL items were found to be comparable to the SF-36 in describing generic HRQOL and performed consistently in the expected direction across demographic subgroups (33). For example, higher income was associated with better health, and women tended to report poorer health across most items than did men. Although the BRFSS measures were able to discriminate between the well group and groups with chronic physical and/or mental conditions, this study lacked enough participants with specific conditions to examine the validity of the items within that context. Analyses of BRFSS data from multiple states compared HRQOL between adults with and without self reported arthritis (34, 35). Compared with those without arthritis, people with self-reported arthritis reported significantly poorer health on all measures. Although these studies highlight the usefulness of the BRFSS items in describing HRQOL in the general population and among those with self-reported arthritis, the evidence for their appropriateness in a clinical population with physician-verified arthritis remains to be determined.

The purpose of this study is to examine the performance of the BRFSS healthy days measures in assessing generic HRQOL in a sample of participants recruited from a clinic population with 3 common rheumatic diseases—fibromyalgia (FM), rheumatoid arthritis (RA), and osteoarthritis (OA).

SUBJECTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

The participants are part of an ongoing longitudinal project measuring rheumatic disease outcomes, approved by the institutional review board of the medical school at the University of North Carolina at Chapel Hill (UNC-CH). Consecutive adult rheumatic disease patients from the UNC-CH rheumatology clinic and selected private rheumatology practices in North Carolina who agreed to participate in the study completed an informed consent form and a baseline self-report health status questionnaire. The participants' physicians provided diagnosis and disease onset at the time of study enrollment. Every 6–12 months, participants are mailed self-report questionnaires designed to assess health status and related variables.

This study population consists of 1,759 participants with OA (n = 456), RA (n = 834), or FM (n = 469) who were sent a questionnaire in October 1999 (Figure 1). Of these, 25 participants who had a primary diagnosis of RA and a secondary diagnosis of OA or FM were classified as having RA for purposes of this study. Twenty-one participants with FM also had a diagnosis of OA and were classified as having FM.

thumbnail image

Figure 1. Study sample flowchart. OA = osteoarthritis; RA = rheumatoid arthritis; FM = fibromyalgia.

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Participants were sent a packet containing a cover letter, a self-report questionnaire, and a business reply envelope. Three weeks after the initial mailing, a postcard was mailed to all participants thanking those who had completed the questionnaire and encouraging nonresponders to complete and return the questionnaire. Three weeks after the postcards were mailed, or approximately 6 weeks after the initial mailing, nonrespondents were sent another questionnaire packet. Six weeks later, another postcard reminder was sent to nonrespondents. Participants with RA were called after the final postcard was sent because RA was the primary focus of the original study.

Of those sent the questionnaire, 741 (42%) participants completed and returned the questionnaire. The response rates by diagnosis were 39% for OA, 47% for RA, and 37% for FM. Participants with RA had a significantly higher response rate than those with OA and FM (χ2 = 16.9, 2 degrees of freedom [df], population size [N] =1,759). Responders were compared with nonresponders in univariate tests on sex, age, education, functional ability, pain, fatigue, and helplessness (see next section for a description of measures). Compared with nonresponders, responders were younger, had more years of education, better functional status, and less pain, fatigue, and helplessness. In a multiple logistic regression analysis, including diagnosis and the aforementioned variables, only age and education were significantly and independently associated with likelihood of responding.

In the final sample, participants who had missing data on any outcome variable (generic or condition-specific health status) were excluded from the analysis (n = 87). Missing data values for disease duration (n = 38) were imputed using the Markov Chain Monte Carlo method (36). Missing values for age, education, and chronic conditions were not imputed because it is likely that the probability of nonresponse for these variables is related to a participant's standing on that variable. Thus, observations with missing data on age, education, and chronic conditions were excluded from the analysis (n = 35). The final study sample of 619 included 133 participants with OA, 334 with RA, and 152 with FM.

BRFSS healthy days measures.

The BRFSS healthy days items, shown in Table 1, were used to assess generic health status (29, 30, 33). A global health item asks individuals to rate their general health as “excellent,” “very good,” “good,” “fair,” or “poor,” and is coded from 1 to 5, with higher scores indicating poorer health. A physical health item asks the respondent to think about physical health, including physical illness and injury, and provide the number of days in the past 30 when physical health was not good. A mental health item, which includes stress, depression, and problems with emotions, asks about the number of days when mental health was not good. The limited activity item asks about the number of days on which poor physical and mental health prevented usual activities such as self care, work, or recreation. Scores on the healthy days items range from 0 to 30, with higher scores indicating poorer health. It should be noted that this measure was administered via mailed questionnaire but the BRFSS HRQOL items are usually administered via telephone interview.

Table 1. Behavioral Risk Factor Surveillance System health-related quality of life core items
Self-perceived health
Would you say that in general your health is
□Excellent
□Very good
□Good
□Fair
□Poor
Recent physical health
Now thinking about your physical health, which includes physical illness and injury, for how many days during the past 30 days was your physical health not good?   days
Recent mental health
Now thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?   days
Recent physical limitations
During the past 30 days, for about how many days did poor physical or mental health keep you from doing your usual activities, such as self care, work, or recreation?   days

Condition-specific measures.

The condition-specific measures represent standard measures regularly used in rheumatologic clinical care and research to assess important aspects of rheumatic disease.

Physical disability.

The Modified Health Assessment Questionnaire (MHAQ) was used to assess the degree of difficulty in performance of 8 basic activities of daily living (ADLs) (37). Reported performance of each activity was coded from 1 to 4, where 1 = “without any difficulty,” 2 = “with some difficulty,” 3 = “with much difficulty,” and 4 = “unable to do.” Scores on the MHAQ were computed as the unweighted mean of the 8 items, with higher scores indicating greater disability.

Pain.

A 10-cm visual analog scale (VAS) was used to assess the amount of pain experienced over the past week on a scale of 0 = “no pain” to 10 = “pain as bad as it could be.”

Fatigue.

A 10-cm VAS was used to assess the degree to which unusual fatigue or tiredness has been a problem over the past week on a scale of 0 = “no problem” to 10 = “a major problem.”

Helplessness.

The 5-item subscale of the Rheumatology Attitudes Index (RAI) was used to measure participants' helplessness (38–40). Theoretically similar to the psychological construct of learned helplessness (41, 42), the RAI provides insight into the degree to which participants feel overwhelmed or lack control of their disease. The response set for each item ranges from 1 = “strongly disagree” to 5 = “strongly agree,” with higher scores indicating greater helplessness. Scores on the measure are computed as the unweighted mean of the 5 items.

Covariates.

The covariates included in the study were sex, age, education, disease duration, and number of chronic conditions. Education was measured in years, and disease duration was measured as the number of years from disease onset to the mailed questionnaire. Year of disease onset was collected from the participant's rheumatologist at the time of enrollment. Participants indicated whether they had any of the following chronic conditions: heart disease, high blood pressure, lung disease, diabetes, ulcer or stomach disease, kidney diseases, liver disease, anemia or other blood disease, cancer, and depression. Positive responses were summed to provide a count of chronic conditions.

Analyses.

Descriptive statistics were performed and univariate analyses were used to assess differences in sociodemographic and health-related covariates among the diagnoses. A series of multiple linear regression models was used to examine how different health status measures varied among the 3 diagnoses. In each model, diagnosis was used as the primary explanatory variable while controlling for age, sex, education, duration of disease, and number of chronic conditions. Initially, these models were fit with individual condition-specific measures (MHAQ, pain, fatigue, and RAI) as the outcome variable. This process was then repeated with the BRFSS items as the outcome.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Descriptive statistics for the sample.

The population had a mean age of 59.1 years and was predominately female and white (Table 2). The means for education and disease duration were 13.7 and 10.1 years, respectively. The mean number of chronic conditions was 1.45, with 45% of participants reporting 2 or more conditions. Comparisons across the 3 diagnoses show significant differences for age (F[2,616] = 35.2, P < 0.0001), sex (χ2 = 28.1, 2 df, N = 616, P < 0.0001), education (F[2,616] = 4.6, P = 0.011), number of chronic conditions (F[2,616] = 3.2, P = 0.042), and disease duration (by multiple imputation procedure). The OA group was the oldest, followed by the RA and FM groups. OA participants had significantly more years of education than those with RA, but not more than those with FM. There was no difference in education between participants with RA and FM. RA participants had significantly longer disease duration and reported fewer chronic conditions than those with FM and OA, but those with FM and OA did not differ on these measures.

Table 2. Sociodemographics for study sample overall and by diagnosis*
CharacteristicOverall (n = 619)Fibromyalgia (n = 152)Rheumatoid arthritis (n = 334)Osteoarthritis (n = 133)
  • *

    Mean values are presented for all variables except when percentages are noted. Numbers in parentheses beside means are standard deviations.

  • N = 599, fibromyalgia n = 145, rheumatoid arthritis n = 326, osteoarthritis n = 128.

  • Missing values for disease duration (n = 38) were imputed using the Markov Chain Monte Carlo method (36).

Age, years59.1 (12.7)52.8 (10.8)59.8 (12.6)64.6 (11.8)
Sex, % female77.492.371.375.2
Race, % white87.090.385.387.5
Education, years13.7 (2.8)13.8 (2.7)13.4 (2.8)14.2 (2.8)
Disease duration, years10.1 (8.1)9.2 (7.5)11.6 (8.5)7.7 (7.0)
Chronic conditions1.45 (1.17)1.64 (1.17)1.36 (1.18)1.48 (1.16)

HRQOL of the sample.

Overall scores on the health status measures are presented in Table 3. MHAQ scores suggest that, on average, participants have relatively little difficulty performing ADLs. Most participants reported a notable amount of pain and fatigue, 5.1 and 5.3, respectively, on a scale from 0 to 10 and experienced moderate helplessness on a 1–5 scale. With a mean level of 3.4 on a 1–5 scale, 43% of the sample reported poor or fair health on the self-perceived health item. For the average participant, almost 40% of the days in the prior month were marked by a perception of poor physical health. In addition, participants reported an average of 8.5 days of poor mental health and 8.2 days out of the previous 30 of activity limitations due to poor physical or mental health.

Table 3. Descriptive statistics on health status measures for entire sample (N = 619)*
 MeanSDObserved range
  • *

    Potential ranges are presented in parentheses beside each variable. MHAQ = Modified Health Assessment Questionnaire; VAS = visual analog scale; RAI = helpless subscale of the Rheumatology Attitudes Index; BRFSS = Behavioral Risk Factor Surveillance System.

Condition-specific measures   
 MHAQ (1–4)1.60.541–4
 Pain VAS (0–10)5.12.80–10
 Fatigue VAS (0–10)5.33.20–10
 RAI (1–5)2.70.941–5
BRFSS healthy days measures   
 Self-perceived health (1–5)3.40.941–5
 Physical health not good (0–30)11.810.80–30
 Mental health not good (0–30)8.510.30–30
 Activities limited (0–30)8.210.20–30

Variations in condition-specific health status measures.

The results of the multiple linear regression analyses on the condition-specific health status measures are shown in Tables 4 and 5. The parameter estimates, t-statistics, and P-values for differences between means are shown in Table 4 and the adjusted means from these models are shown in Table 5. Among the 3 diagnoses, there were only marginal differences in physical disability as measured by the MHAQ. However, pain, fatigue, and helplessness differed markedly between those with FM and those with OA and RA, with FM patients reporting the worst health. Those with RA and OA differed marginally on pain and not at all on fatigue and helplessness.

Table 4. Parameter estimates for differences between means by diagnosis for condition-specific measures*
MeasureFM versus RAFM versus OARA versus OA
βtPβtPβtP
  • *

    FM = fibromyalgia; RA = rheumatoid arthritis; OA = osteoarthritis; MHAQ = Modified Health Assessment Questionnaire; VAS = visual analog scale; RAI = helplessness subscale of the Rheumatology Attitudes Index.

MHAQ0.010.210.83260.111.810.06960.101.950.0518
Pain VAS1.405.22<0.00010.092.760.0058−0.49−1.760.0777
Fatigue VAS1.525.36<0.00011.574.51<0.00010.050.170.8669
RAI0.374.17<0.00010.403.660.00020.030.320.7469
Table 5. Adjusted means on condition-specific measures by disease diagnosis*
MeasureFibromyalgiaRheumatoid arthritisOsteoarthritis
  • *

    Means adjusted in multiple linear regression that includes age, sex, education, disease duration, and number of chronic conditions.

  • MHAQ = Modified Health Assessment Questionnaire; VAS = visual analog scale; RAI = helplessness subscale of the Rheumatology Attitudes Index.

MHAQ1.671.661.56
Pain VAS6.004.605.10
Fatigue VAS6.444.924.87
RAI2.992.622.59

Variations in the BRFSS healthy days measures.

Responses to the BRFSS healthy days measures were examined among the 3 rheumatic disease diagnoses using multiple linear regression (Table 6). Adjusted means from these models are shown in Table 7. There were significant differences among the 3 diagnoses in self-reported health. A similar analysis was performed treating the self-perceived health item as a dichotomous variable and using multiple logistic regression. Participants were divided into those with fair or poor health versus excellent, very good, or good health. The results of the analysis were consistent with results from the multiple linear regression described here.

Table 6. Parameter estimates for differences between means by diagnosis for the BRFSS HRQOL measures
MeasureFM versus RAFM versus OARA versus OA
βtPβtPβtP
  1. * BRFSS = Behavarial Risk Factor Surveillance System; HRQOL = health-related quality of life; FM = fibromyalgia, RA = rheumatoid arthritis, OA = osteoarthritis.

Self-perceived health0.253.080.00210.565.54<0.00010.313.590.0003
Physical health not good3.783.730.00025.514.43<0.00011.741.650.0983
Mental health not good4.995.28<0.00015.654.87<0.00010.660.680.4980
Activities limited2.973.100.00193.723.160.00160.750.750.4531
Table 7. Adjusted means on the BRFSS HRQOL measures by disease diagnosis
MeasureFibromyalgiaRheumatoid arthritisOsteoarthritis
  1. * Means adjusted in multiple linear regression that includes age, sex, education, disease duration, and number of chronic conditions. BRFSS = Behavioral Risk Factor Surveillance System; HRQOL = health-related quality of life.

Self-perceived health3.623.373.06
Physical health not good15.0111.239.49
Mental health not good12.387.406.73
Activities limited10.607.636.88

Participants with FM reported higher scores (indicating poorer health) than those with OA and RA, and participants with RA reported poorer health than those with OA. There were also significant differences in the number of poor physical health days, poor mental health days, and limited activity days according to disease diagnosis. For these 3 items, participants with FM reported poorer health than those with RA and OA. There were no significant differences between participants with RA and OA on these measures.

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Two principal observations derive from this investigation. First, the BRFSS healthy days measures performed well in a clinic population with physician-diagnosed rheumatic disease. In addition, the measures detected interesting differences among rheumatic disease diagnoses. These findings provide support for using the BRFSS healthy days measures in research in clinical populations with rheumatic conditions.

The ability of the BRFSS items to describe and differentiate among those with varying degrees of HRQOL within the general population has been established. Either of 2 approaches could have been used to validate these generic measures in a clinical arthritis population: 1) demonstration of construct validity via the theoretically based framework established in measurement development; and 2) establishment of criterion validity by comparing a measure against a gold standard. Both approaches have been taken with the BRFSS HRQOL items in the general population but not specifically in individuals with rheumatic disease. Guyatt and colleagues noted that the goals of an HRQOL measure include discrimination between different degrees of HRQOL at a single point in time (43). In the present investigation, a related approach to validation was chosen: Examination of whether the BRFSS HRQOL items describe and differentiate among individuals with different rheumatic diseases.

These data suggest that generic measures perform as well as condition-specific measures in discriminating poor HRQOL among individuals with OA, RA, and FM. The relatively poor health reported by our clinic population is consistent with the poorer health reported by individuals with self-reported arthritis from a population-based sample (34). HRQOL based on the condition-specific measures differed, for the most part, by diagnosis. The exception was the MHAQ, where scores did not differ among the 3 diagnoses. However, participants with FM reported higher levels of pain, fatigue, and helplessness than participants with OA and RA. These observations are consistent with previous assessments of illness in FM. Interestingly, scores on the BRFSS HRQOL items also indicated differences among the diagnoses. Compared with OA and RA patients, FM patients reported poorer perceived health, more days of poor physical and mental health, and more activity-limited days.

Our study has several limitations. First, recall periods for the various measures differed. This discrepancy in recall time is common when using multiple self-report measures and is inherent in the measures. However, as Baldwin notes, self-report data are a valuable resource, and the problems encountered with self-report data are similar to those encountered in other forms of data collection (44). Second, the response rate for this study was relatively low and differed by diagnosis. In comparisons between responders and nonresponders, only age and education were significantly independently associated with likelihood of responding. The main analyses were adjusted for these variables, making it unlikely that they are responsible for differences in health status by diagnosis. Third, the moderate response rate, coupled with the underlying sociodemographics of the clinic population, resulted in a predominately white, well-educated sample. Attempts should be made to expand to more diverse populations in future studies.

In summary, this study provides clear evidence that the BRFSS healthy days items provide a useful and convenient instrument for describing HRQOL in a population of individuals with arthritis from a clinical setting. Furthermore, differences in HRQOL among diagnosis groups that were established using condition-specific measures were mirrored on the BRFSS healthy days items. Use of these items for populations with arthritis is supported by these findings, which is encouraging given the current prominent role of the BRFSS healthy days measures in assessing the burden of disease in arthritis.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

The authors thank Julie Keysor, Jennifer Milan Polinski, and Kim O'Neill for their help in collecting and organizing data, working with participants, and providing valuable input for this project. We would also like to thank the following physicians for encouraging their patients to participate in our database and outcomes studies: H. Vann Austin, Franc Barada, Robert Berger, Mary Anne Dooley, William Gruhn, Robert Harrell, Tatiana Huguenin, Beth Jonas, Joanne Jordan, Fathima Kabir, Elliott Kopp, Andrew Laster, Kara Martin, Gwenesta Melton, Nicholas Patrone, Kate Queen, Westley Reeves, Hanno Richards, Alfredo Rivadeneira, William Rowe, Gordon Senter, Paul Sutej, Claudia Svara, Anne Toohey, William Truslow, and William Yount.

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  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. SUBJECTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
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