- Open Access
Comparative assessment of three different indices of multimorbidity for studies on health-related quality of life
© Fortin et al; licensee BioMed Central Ltd. 2005
Received: 29 September 2005
Accepted: 23 November 2005
Published: 23 November 2005
Measures of multimorbidity are often applied to source data, populations or outcomes outside the scope of their original developmental work. As the development of a multimorbidity measure is influenced by the population and outcome used, these influences should be taken into account when selecting a multimorbidity index. The aim of this study was to compare the strength of the association of health-related quality of life (HRQOL) with three multimorbidity indices: the Cumulative Illness Rating Scale (CIRS), the Charlson index (Charlson) and the Functional Comorbidity Index (FCI). The first two indices were not developed in light of HRQOL.
We used data on chronic diseases and on the SF-36 questionnaire assessing HRQOL of 238 adult primary care patients who participated in a previous study. We extracted all the diagnoses for every patient from chart review to score the CIRS, the FCI and the Charlson. Data for potential confounders (age, sex, self-perceived economic status and self-perceived social support) were also collected. We calculated the Pearson correlation coefficients (r) of the SF-36 scores with the three measures of multimorbidity, as well as the coefficient of determination, R2, while controlling for confounders.
The r values for the CIRS (range: -0.55 to -0.18) were always higher than those for the FCI (-0.47 to -0.10) and Charlson (-0.31 to -0.04) indices. The CIRS explained the highest percent of variation in all scores of the SF-36, except for the Mental Component Summary Score where the variation was not significant. Variations explained by the FCI were significant in all scores of SF-36 measuring physical health and in two scales evaluating mental health. Variations explained by the Charlson were significant in only three scores measuring physical health.
The CIRS is a better choice as a measure of multimorbidity than the FCI and the Charlson when HRQOL is the outcome of interest. However, the FCI may provide a good option to evaluate the physical aspect of HRQOL for the ease in its administration and scoring. The Charlson index may not be recommended as a measure of multimorbidity in studies related to either physical or mental aspects of HRQOL.
The coexistence of multiple chronic diseases in the same individual or multimorbidity has led to increasing interest in its measure in research studies as a potential confounder or as a predictor of study outcome [1, 2].
Health-related quality of life (HRQOL) is an outcome measure that is adversely affected by the presence of multimorbidity. This association can be demonstrated using the simple count of chronic conditions as a measure of multimorbidity [3–8]. However, we found in a recent study that the use of a multimorbidity index, the Cumulative Illness Rating Scale (CIRS), revealed a stronger association of HRQOL with multimorbidity than a simple count of chronic diseases . Measures of multimorbidity are often applied to source data, populations or outcomes outside the scope of the original developmental work . However, as the development of a multimorbidity measure is influenced by the population and outcome used, these influences should be taken into account when selecting a multimorbidity index . Although the CIRS is a comprehensive evaluation of medical problems by organ system, it was not developed in light of HRQOL. Therefore, it can be argued that another measure of multimorbidity (or comorbidity if an index disease is the object of study) specifically designed for HRQOL could bear a stronger relationship with HRQOL than the CIRS, and would be a better measure of multimorbidity when the outcome of interest is HRQOL.
Several indices have been described to measure multimorbidity or comorbidity [1, 2, 11]. However, some problems related to many of these indices have been reported such as insufficient data on their clinimetric properties and moderate inter-rater reliability [2, 12]. Two indices stand out as potential alternatives to the CIRS, the Charlson Index and the Functional Comorbidity Index (FCI). The Charlson index  is, with the CIRS , among the most valid and reliable measures of multimorbidity . The Charlson index is the most extensively studied comorbidity index and, although the weights originally used to develop it were based on the relative risk of dying, it has been found to significantly predict the number of ambulatory visits, the probability of an inpatient admission, the length of stay, and hospital costs [9, 15]. However, the association between the Charlson index and HRQOL has been assessed only in patients of age 65 or older . Recently developed, the Functional Comorbidity Index (FCI)  was specifically developed with physical functioning, an aspect of HRQOL, as the validity criterion. The index was developed using two databases totalizing 37,772 Canadian and US adults seeking treatment for spine ailments. It is possible that the association of this index with physical aspects of HRQOL could outperform the CIRS, but this hypothesis has not been tested yet.
Using these three indices (CIRS, FCI and Charlson) on the same target population would allow a better comparison of their performance when the outcome of interest is HRQOL, but we could not find any study with such comparison. Thus, the primary purpose of this study was to compare the strength of the association of the CIRS, the Charlson index and the FCI measures of multimorbidity, with HRQOL.
Characteristics of the Sample
Refusals (n = 115)
Participants (n = 238)
Mean (SD) age, y
Mean (SD) diagnoses, n
Main characteristics of CIRS, FCI and Charlson†
5. Ophthalmological and ORL
6. Upper gastrointestinal
7. Lower gastrointestinal
8. Hepatic and pancreatic
11. Musculoskeletal and tegumental
13. Endocrine, metabolic, breast
1. Arthritis (rheumatoid and osteoarthritis)
4. COPD, ARDS*
6. Congestive heart failure or heart disease
7. Heart attack
8. Neurological disease
9. Stroke or transient ischemic attack
10. Diabetes types I and II
11. Peripheral vascular disease
12. Upper gastrointestinal disease
14. Anxiety or panic disorders
15. Visual impairment
16. Hearing impairment
17. Degenerative disk disease
18. Obesity and/or BMI > 30 kg/m2
1. Myocardial infarct
2. Congestive heart failure
3. Peripheral vascular disease
4. Cerebrovascular disease
6. Chronic pulmonary disease
7. Connective tissue disease
8. Ulcer disease
9. Stroke or transient ischemic attack
12. Moderate or severe renal disease
13. Diabetes with end organ damage
14. Any tumor
17. Moderate or severe liver disease
18. Metastatic solid tumor
All systems weighted from 0 to 4:
0 No problem
4 Extremely severe
Presence (yes) or absence (no) of diagnoses
Conditions from 1 to 10, weight = 1
Conditions from 11 to 16, weight = 2
Condition 17, weight = 3
Conditions 18 and 19, weight = 6
Sum of weights assigned to each system
Sum of "yes" answers
Sum of weights assigned to each condition that a patient has
Data for potential confounders (age, sex, self-perceived economic status and self-perceived social support) were also collected. Self-perceived social support was measured with the Social Provisions Scale . The research ethics board of the Centre de santé et de services sociaux de Chicoutimi approved this study.
To investigate the relationship between HRQOL and the multimorbidity indices as well as the direction of the relationships (positive or negative), we first calculated the Pearson correlation coefficients of the SF-36 scores with the three measures of multimorbidity. We also compared CIRS correlation coefficients with those of the FCI and the Charlson index . Next, the coefficient of determination, R2, was calculated to measure the percentage of variation in the dependent variables (all SF-36 scales and two SF-36 summary scores) explained by each measure of multimorbidity over and above that explained by age, gender, self-perceived social support and self-perceived economical status. We obtained these estimates through multiple regression analysis for which underlying assumptions were judged satisfactory. All analyses were done using the SAS system for Windows (version 8.02, SAS Institute, Inc, Cary, NC, USA).
After standardization of the scoring process, the intraclass correlation coefficients for the inter-rater reliability were 0.96, 0.92 and 0.90 for the CIRS, the FCI and the Charlson respectively.
Pearson correlation coefficients of the SF-36† scores with the measures of multimorbidity
Correlation coefficients (r)
Physical Component Summary
Mental Component Summary
Percentage of variation of the SF-36 ◇ scores explained by each measure of multimorbidity
Percentage of variation explained by the control variables†
Physical Component Summary
Mental Component Summary
We compared the strength of association of three multimorbidity indices (CIRS, FCI and Charlson index) with HRQOL as the outcome of interest in a primary care context. In terms of percent of explained variation in HRQOL, the CIRS performed as well as and often better than the FCI and the Charlson index in all scores of the SF-36. Correlation coefficients of the SF-36 scores with the measures of multimorbidity were always higher for the CIRS, followed by the FCI (Table 3); the correlations of the SF-36 scores with the Charlson index were always the weakest. We also found an unexpected positive correlation of the Charlson index with the SF-36 Mental Component Summary.
Among the three indices, the CIRS was the one that explained the highest percent of variation in all scores of the SF-36. Despite the fact that the FCI was developed with physical function as the outcome of interest, it did not perform better than the CIRS in any of the scales of the SF-36 evaluating the physical aspect of HRQOL. This result may be due in part to the wider range of possible scores on the CIRS. Indeed, an index ranging from 0 to 27 can better predict variations in an outcome than one that ranges from 0 to 7 or 8 with more than half the patients being classified in the first 2 or 3 levels of the scale. It may also be due to the fact that the CIRS evaluates the number and severity of all chronic diseases whereas the FCI evaluates a limited number of diagnoses and does not take into account disease severity. However, R2 values for the FCI related to physical health scores, although lower than those of the CIRS, remained highly significant after controlling for confounders. Given that the FCI is very easy to administer and score, researchers may consider, depending on the characteristics of the study, to trade off a lower explained variation for simplicity to evaluate the physical aspect of HRQOL. In the case of the Charlson index, the percent of explained variation was significant only in the Physical Functioning, the General Health, and the Physical Component Summary scales. In the mental aspect of HRQOL, the percent of variation explained by the Charlson index was not significant in any of the scales of the SF-36. Given these results, the Charlson index may not be recommended as a measure of multimorbidity in HRQOL studies in adults.
The FCI was the only index of multimorbidity that we were aware of that was developed using a component of HRQOL (Physical Functioning) as outcome. However, two other articles reporting multimorbidity measures related with HRQOL were published upon completion of the present study. One of the articles describes a new self-reported assessment of comorbidity, or self-reported disease burden ; the other article describes five indices or approaches to scoring multimorbidity derived from a self-administered multimorbidity questionnaire .
In the article on the self-reported disease burden , the index was validated using two scales of the SF-36 evaluating the physical aspect of HRQOL (Physical Functioning and one item of General Health) as well as the outcomes of depression and self-efficacy. The authors studied these outcomes using the Charlson index and the findings were similar to ours. They found a negative correlation between the Charlson index and the Physical Functioning and General Health outcomes . However, our study expanded the analysis of the Charlson index to all scales of the SF-36 evaluating both physical and mental aspects of the HRQOL. Moreover, we included adults aged 18 and over, whereas age was restricted to 65 years or older in the study on the self-reported disease burden . In the second paper by Byles et al , the study was a comparison of the performance of five indices derived from a self-administered multimorbidity questionnaire. None of the indices was compared to other indices previously published. Unfortunately, it was not possible to include these five indices in our comparative study because of the chart review method that we used. However, future research comparing CIRS with these five indices as well as with the self-reported disease burden index is warranted.
In our analysis of the relationship between mental aspects of HRQOL and multimorbidity, we found some contradictory results that may reflect a limitation in our instruments. All scales of the SF-36 used to measure the mental aspect of HRQOL were related to the CIRS, whereas the Mental Component Summary was not (Tables 3 and 4). This summary score was created by the developers of the SF-36 with the hope to reduce the number of statistical comparisons involved in analyzing the SF-36 without substantial loss of information . The lowest possible score of the Mental Component Summary indicates frequent psychological distress, social disability due to emotional problems, and a poorly self-rated health . However, the lack of relationship we found between the CIRS and the Mental Component Summary contradicts the relationship we found between the CIRS and all mental scales of the SF-36 of which the Mental Component Summary is a composite. One possible explanation may be that the calculation of the Mental Component Summary takes into account not only the four scales measuring mental health, but also the four scales measuring physical health which are weighted negatively . As a result, the positive weights of the mental health scales may be canceled out by the negative weights of the physical health scales which have a stronger relationship with the CIRS in our study. This problem was evident in the relationship between the CIRS and the Mental Component Summary, but it also affected the relationships between this summary score and the other measures of multimorbidity. These results suggest that the Mental Component Summary produced a substantial loss of information in the context of our study.
In summary, our study suggests that the CIRS is a better choice as a measure of multimorbidity than the FCI and the Charlson index in a primary care context when HRQOL is the outcome of interest. However, if researchers were interested only in the physical aspect of HRQOL, then the FCI, despite its lower explained variation in HRQOL, may provide a good option for the ease in its administration and scoring. Finally, based on our results, the Charlson index may not be recommended as a measure of multimorbidity in studies related to either physical or mental aspects of HRQOL.
Sources of support: Fonds de la Recherche en Santé du Québec (Grant number: 24300-2028) and Pfizer Canada (Independent Research Grant).
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