This Article Abstract Full Text (PDF) Services Download to citation manager PubMed PubMed Citation

The Relationship Between Medical Comorbidity and Self-Rated Pain, Mood Disturbance, and Function in Older People With Chronic Pain

¹ Department of Geriatric Medicine, Tan Tock Seng Hospital, Singapore.
² Florey Institute, University of Melbourne, Australia.
³ Barbara Walker Centre for Pain Management, St. Vincent's Hospital, Fitzroy, Australia.
⁴ National Ageing Research Institute, Parkville, Australia.

Address correspondence to Ian Y. Leong, FRCP Edinburgh, Consultant, Department of Geriatric Medicine, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore 308433, Singapore. E-mail: ian_leong{at}ttsh.com.sg

	Abstract

Top Abstract Materials and Methods Results Discussion References

 
Background. Aging is associated with greater risk for many illnesses and the prospect of multiple, concurrent disease states. Chronic pain is also very common in advanced age, and there is likely to be a relationship with comorbid burden, but few studies have examined this issue. This study tests the hypothesis that comorbid burden is associated with greater levels of self-reported pain and associated disturbance in mood and function.

Methods. Psychometric and medical data were collected from 562 patients (mean age = 76.3 years) attending a geriatric pain clinic. The number of categories endorsed on the Cumulative Illness Rating Scale (CIRS) score was used to measure accumulated comorbid burden. These groups were tested for differences in the severity of self-reported pain. The predictive capacity of comorbid burden for explaining variance in mood disturbance and functional disability was assessed after controlling for any differences in age and severity of pain.

Results. Over 50% of the sample had three or more comorbid problems. Groups with greater levels of comorbidity scored higher on the Present Pain Intensity Index, the sensory and affective subscales of the McGill Pain Questionnaire. Multiple regression analysis showed that the CIRS score explained a significant proportion of the variance in scores on the Geriatric Depression Scale (4.1%), Human Activities Profile (4.8%), and the physical domain of the Sickness Impact Profile (5.9%).

Conclusion. Greater levels of comorbidity are associated with reports of more severe pain, more depressive symptoms, reduced activity levels, and higher physical impact from pain.

Multiple comorbid disease burden is a hallmark of geriatric medicine and an extremely common occurrence in older adults. Prevalence estimates vary according to the population under study and the measures used, but a simple count of the number of coexistent diseases suggests that the majority of community dwelling older adults will suffer from four or more comorbid medical problems (10,11). It is widely recognized that comorbidity has a negative impact on physical health, emotional, cognitive, and functional status that goes beyond the mere combined sum effect of each individual disease (11–13). From a clinical perspective, comorbidity is important because it strongly influences the diagnostic process by modifying the clinical presentation of other coexistent medical complaints. As a result, it would seem worthwhile to examine any potential relationship between the presence of medical comorbidity and the phenomenology of chronic pain in adults of advanced age.

There have been relatively few empirical studies to examine the relationship between pain report and the burden of medical comorbidity. Experimentally, pain thresholds are known to be increased in the presence of hypertension; this may result in a diminished pain report (13,14). Esposito (15) reported less frequent pleuritic chest pain as a presenting symptom of pneumonia in older adults with a high level of coexistent disease. In contrast, in a study of hospitalized patients, comorbid burden as measured by the Charlson Index was associated with an increased risk (odds ratio = 1.03) for reports of moderate to severe acute pain (16). There is also a paucity of evidence with respect to comorbid burden, chronic pain, and associated emotional suffering and disability. Farrell and colleagues (17) reported greater pain-related impact on activity and a higher number of depressive symptoms in chronic pain patients with more than three comorbid medical complaints. However, when compared to pain reports of patients with none, one, or two complaints, pain reports did not differ in those with three or more comorbid problems. Using cluster analysis, Corran and colleagues (18) showed that there is a group of older pain clinic patients that have relatively low pain, but high levels of disability and depressive symptoms. The authors subsequently reported that this group had a much higher degree of medical comorbidity (19). However, a cluster analysis based on the Multiaxial Assessment of Pain system did not find any differences in terms of nonpainful medical pathology between groups of older pain patients differing in the severity of pain and its psychosocial impacts (20). Collectively, these studies emphasize a possible relationship between medical comorbid burden, pain report, and levels of emotional and functional well-being, although the magnitude and direction of these effects remain somewhat unclear.

The aims of the current study were to (a) examine the extent of comorbid disease in older adults with chronic pain referred to a multidisciplinary pain management service, (b) compare the levels of self-reported pain in groups defined by the extent of comorbid disease burden, and (c) explore the relationship between medical comorbidity and self-rated mood disturbance and functional impact, after controlling for variations in age and pain.

	MATERIALS AND METHODS

Top Abstract Materials and Methods Results Discussion References

 
Study Design
This study was a retrospective, cross-sectional analysis of a sample from a pain clinic for older people at the Melbourne Extended Care and Rehabilitation Services. The clinic is a tertiary referral outpatient pain management service affiliated with the National Aging Research Institute and the University of Melbourne, Australia. Patients underwent a multidisciplinary assessment over the course of two sessions, which included an evaluation by a physician (geriatrician or neurologist), a physiotherapist, and a clinical psychologist. Thereafter, an individualized treatment program was designed. The client population and management outcomes of the clinic have been documented elsewhere (21).

Sample
Most patients were community-dwelling older people. From 1991 to 1999, 562 patients aged 65 years and older were assessed; 538 patients had complete scores on the Cumulative Illness Rating Scale (CIRS). Complete psychometrics could not always be obtained due to language problems, a failure to understand due to educational deficiencies, or noncompliance with the returning of data forms. Therefore, the final sample represents English-speaking, older Caucasian Australians.

Data Collection
In addition to demographic information, the following data were collected:

1. The modified CIRS was used to measure comorbid burden (22). The CIRS score, depending on the version, takes into account impairment in 13 or 14 organ systems. Each organ system is given a score from 0 (no organ impairment) to 4 (extremely severe organ impairment). Two types of scores can be calculated for the CIRS. Impairment scores for each system can be tallied into a composite score, or a simple total can be generated from summing the number of categories endorsed. The CIRS has good inter-rater correlation (0.82, Kendall's W). The CIRS score has been shown to correlate with mortality, hospitalization rates and duration, hospital readmission rates, medication usage, functional disability, and patient morale in a geriatric population (13,23). In our clinic, the version of the CIRS has been modified to document the following categories of organ impairment: cardiac, respiratory, eyes/ear/nose/throat, gastrointestinal, urological/renal, musculoskeletal, neurological, psychiatric, endocrine, hematological, dermatological, dementia, hepatic, and cancer (any site). This modification was adopted as it was felt to better reflect the variety of organ impairment in the population seen at the clinic. The number of organ systems was adopted as the scoring method. In this study, we have defined comorbid burden as the burden of additional illnesses; that is, the number of organ impairments apart from that which resulted in the pain diagnosis. In addition, we excluded psychiatric diagnoses to obviate the possibility of inflated associations when using the CIRS scores to predict symptom levels of depression, anxiety, and pain.
   
2. The McGill Pain Questionnaire represents 20 groups of word descriptors ordered by the intensity of sensation. The Pain Rating Index (sensory) (PRIS) describes the sensory quality of pain (e.g., hot-burning, aching, shooting, stabbing, stinging, pounding), and the Pain Rating Index (affective) (PRIA) was used to evaluate the unpleasantness or affective dimensions of the pain report (e.g., sickening, tiring, cruel, frightful, annoying). The Present Pain Intensity Index (PPI) score represents an overall cognitive appraisal of the pain severity (e.g., mild, discomforting, distressing, horrible, excruciating) and was recorded during the initial visit.
   
3. The Geriatric Depression Scale (GDS) was used to measure depressive symptoms (24). The GDS is a 30-item questionnaire used for screening for depression in the older person. A score of 11–20 is suggestive of mild to moderate depression, and a score of 21 or above is suggestive of severe depression. It has been extensively used and validated in multiple geriatric settings (25).
   
4. The state portion of the Spielberger State-Trait Anxiety Inventory (STAI) was used to measure symptoms of anxiety (26). It consists of 20 items with each item being scored on a 4-point Likert scale. Increasing scores suggest increasing severity of anxiety symptoms. A score of 38 or above for women and a score of 40 or above for men represents the standard cut-point for anxiety disorder in adults aged 50–69 years (26). These cut-off values have been confirmed in other studies of geriatric patients up 96 years of age (27) and so were used to demarcate a case of high anxiety in the current study.
   
5. The Sickness Impact Profile (SIP) was used as a self-report measure of pain-related disability (28). The SIP contains 136 items relating to 12 categories, which can be summarized into scores relating to two domains: physical and psychosocial. The physical domain consists of the following categories: ambulation, mobility, body care, and movement. The psychosocial domain consists of the following categories: social interaction, communication, alertness behavior, emotional behavior, sleep and rest, eating, home management, recreation and pastimes, and employment. In our study, we analyzed the scores for the physical and psychological dimensions separately. Patients were instructed to score items as they related to the impact of pain.
   
6. The Human Activities Profile (HAP) was used to measure activity level (29). The HAP consists of 94 activities in ascending order of metabolic demand. Participants endorsed one of three alternatives for each item: they continued to perform the activity, they had discontinued the activity, or they have never performed the activity. Several types of scores can be calculated from the HAP. Our study used the Adjusted Activity Score, which represents the number of activities nominated as "still doing this activity." The performance of the HAP has been tested in older pain clinic patients, where it demonstrated sound reliability and construct and discriminative validity (30).
   

Statistical Analysis
The data were analyzed using SPSS version 10.1 (SPSS, Chicago, IL). Frequencies and descriptive statistics of the demographic and illness data of the study population were calculated. A one-way analysis of variance (ANOVA) was used to analyze the difference in scores of PPI, PRIA, and PRIS between groups defined by increasing levels of comorbidity. The Scheffe test was used in the post hoc analysis to determine the significance of any differences among groups.

Multiple regression was used to estimate the variance of HAP, SIP (physical), SIP (psychosocial), GDS, and STAI scores that could be accounted for by the CIRS score after controlling for the contribution of age and pain (PPI, PRIS, and PRIA). In the analysis of the HAP, SIP (physical), GDS, and STAI scores, there was no violation of the assumptions of linearity, normality, and homoscedasticity. As the SIP (psychosocial) was found to be positively skewed, a logarithmic transformation was performed. Age was included as an independent variable as it was felt to be closely associated with comorbidity, and comorbidity may well be a surrogate for chronological age in our sample. Age was entered in the first step, followed by the pain variables (PPI, PRIA, PRIS) in the next step. The CIRS score was entered at the last step to obtain the independent contribution of the CIRS after controlling for variations in age and self-rated pain. Individual R² change was reported to demonstrate the variance contributed by the variables in each step. The standardized ß coefficient was reported to compare the relative importance of each independent variable (i.e., age, pain, CIRS scores) in the prediction of the dependent measures (depression, anxiety, functional impact). The standardized ß coefficient can be interpreted as the change in the dependent variable of interest (i.e., age, pain, CIRS scores) for each 1 standard deviation (SD) change in the predictor.

	RESULTS

Top Abstract Materials and Methods Results Discussion References

 
The demographic data for the sample are reported in Table 1. More than 50% of the sample endorsed clinically significant levels of depressive and anxiety-related symptoms. The type of organ system involvement and the number of organs involved are shown in Table 2. Over 50% of the sample had three or more systems affected by comorbid disorders, (i.e., disease apart from the disorder resulting in pain). The main cause of pain after evaluation by the multidisciplinary team was osteoarthritis in 30.3% of patients (see Table 3).

	DISCUSSION

Top Abstract Materials and Methods Results Discussion References

To our knowledge, this is the first study to demonstrate an association between the extent of comorbid burden and the severity of self-reported pain. In particular, post hoc analyses revealed that, irrespective of the pain measure used (i.e., PPI, PRIS, PRIA), it was always the group with four or more medical comorbidities that exhibited significantly higher mean pain scores, whereas the groups defined by zero, one, two, or three comorbid problems did not differ from each other. Why should nonpainful comorbid burden be associated with increased pain report? Thus far, comorbid hypertension is one of the few medical disorders in which a consistent relationship has been found with pain report (14). However, increasing levels of blood pressure are associated with reduced pain sensitivity, whereas the current findings demonstrate increased pain in those individuals with high comorbid burden. There are some obvious differences between the potential impact of a single disease versus overall comorbid burden, and this may help explain the discrepancy. Another question that remains to be answered is why patients with four or more comorbid medical problems seem to be those that differ in terms of the severity of pain report? Why not patients with three or more or two or more comorbid problems? Although highly speculative, increased comorbidity is strongly associated with frailty (31), and frailty is defined as a point at which lack of physiologic reserve results in clinically observable disorders (31). Perhaps comorbidity shares a similar common pathway, and a certain incremental point of comorbid burden needs to be reached before the impact has clinically observable consequences.

The association of comorbid burden and self-reported depression and anxiety in older people has been examined in prior studies. In terms of comorbid burden and depressive symptoms, Penninx and colleagues (32) showed an association between number of chronic diseases and depressive symptoms, with specific comorbidities accounting for 5.2% of the variance in depressive symptom scores. Lyness and colleagues (33) also reported the CIRS score as contributing 3.8% of the variance of the GDS score and 7.9% of the variance in the Hamilton Rating Scale for Depression. The contribution to the variance in depressive symptoms in our study was of a similar magnitude and concurs with previous findings. In terms of anxiety symptoms, Penninx and colleagues (32) also showed that selected comorbidities contributed 3.6% of the variance in anxiety symptom scores. However, we did not demonstrate any contribution by CIRS. One possibility is that the study by Penninx and colleagues was very large (n = 3076), and the enhanced statistical power allowed a small but significant relationship even though the levels of anxiety were within the normal range (3.8 on the Anxiety subscale of the Hospital Anxiety and Depression scale). Another possibility involves the demonstrated differential contribution of the various medical diseases to anxiety symptoms. For example, the severity of self-rated anxiety symptoms was associated with osteoarthritis and rheumatoid arthritis but not with cardiac disease, stroke, or diabetes mellitus (32). The variance in the relationship between self-rated anxiety with rheumatoid arthritis and osteoarthritis was greater than that with lung disease or diabetes mellitus. Thus, it is possible that, after accounting for the independent predictive value of PPI and PRIA to variance in self-rated anxiety, there is little further contribution from other nonpainful comorbid conditions.

The relationship between comorbid burden and physical functioning has been less clearly demonstrated in previous research (34,35). It has been shown that various individual chronic conditions (for example, arthritis, heart disease, cerebrovascular disease, Parkinson's disease, impaired vision) can contribute to an increased physical impairment, but there has been no attempt to examine overall comorbid burden (34,35). Greater comorbid burden would increase the possibility of the concurrent presence of one or more of these chronic conditions and could thereby result in decreased functioning. In our study, comorbid burden contributed to 5.9% of the variance in the physical subscale of the SIP and 4.8% of the HAP, but not to the psychosocial subscale of the SIP. Although the magnitude of explained variance in physical functioning remains relatively modest at around 5%, it was at least double the contribution from age and one third to one half the contribution from self-rated severity of pain. These findings emphasize the relative importance of comorbid burden when characterizing the clinical presentation of chronic pain and associated functional impact. They also suggest that, in the older segments of the population, it may be better to organize multidisciplinary pain management services around comorbidity status rather than around the age of the chronic pain patient.

This study represents an initial exploration into the relationship between comorbid burden and chronic pain and associated emotional disturbance and functional disability. Given the lack of previous research in this area, similar studies are required to validate our findings. Moreover, the retrospective design used in the current study does not allow for tests of causality or to establish the direction of effects. As a result, it remains unclear whether chronic pain increases the susceptibility to other comorbid conditions, whether comorbid burden exacerbates the pain experience, or whether both are true. Psychophysical studies with experimentally controlled levels of noxious stimulation could be used to address this question and help quantify the influence of comorbid burden on pain sensitivity. Further exploration of painful and nonpainful disease states might also be worthwhile to better clarify the precise nature of the relationship between individual disease states, overall comorbid burden, and chronic pain. Finally, it must be acknowledged that the sample used in the current study comes from a multidisciplinary pain clinic that represents a highly select patient group with refractory chronic pain and very high levels of disability and mood disturbance. Future research could also examine a random community population of older adults with presumably lower levels of physical and psychosocial disability to see if the current findings can be generalized to a broader community setting.

Conclusion
Medical comorbid burden is associated with higher reports of pain, lower levels of activity, more physical impact from pain, and greater levels of depressive symptoms in older pain clinic patients. Comorbid illness should be considered as part of the routine clinical assessment of older pain clinic patients and, given the demonstrated relationship, efforts to concurrently manage both chronic pain and comorbid disease should lead to improved treatment outcomes for older persons with chronic pain.

	Acknowledgments

Top Abstract Materials and Methods Results Discussion References

 
This research was supported, in part, by a grant from the National Health and Medical Research Council of Australia (285103).

We acknowledge Dr. Benny Katz and the Melbourne Extended Care and Rehabilitation Services in the collection of the data.

This work was completed at the National Ageing Research Institute, Melbourne, Australia.

	Footnotes

Top Abstract Materials and Methods Results Discussion References

 
Decision Editor: Luigi Ferrucci, MD, PhD

Received January 23, 2006

Accepted August 21, 2006

	References

Top Abstract Materials and Methods Results Discussion References

 

1. Parmelee PA, Smith B, Katz IR. Pain complaints and cognitive status among elderly institution residents. J Am Geriatr Soc. 1993;41:517-522.[Medline]
2. Jones GT, Macfarlane GJ, Edwards RR. Epidemiology of pain in older persons. In: Gibson SJ, Weiner DK, eds. Pain in Older Persons, Progress in Pain Research and Management. Vol 35. Seattle: IASP Press; 2005:3–22.
3. Scudds RJ, McD Robertson J. Empirical evidence of the association between the presence of musculoskeletal pain and physical disability in community-dwelling senior citizens. Pain. 1998;75:229-235.[Medline]
4. March LM. Musculoskeletal disability among elderly people in the community. Med J Aust. 1998;168:439-442.[Medline]
5. Parmelee PA, Katz I, Lawton MP. The relation of pain to depression among institutionalized aged. J Gerontol. 1991;46:P15-P21.[Abstract]
6. Casten RJ, Parmelee PA, Kleban MH, Lawton MP, Katz IR. The relationships among anxiety, depression and pain in a geriatric institutionalized sample. Pain. 1995;61:271-276.[Medline]
7. Mossey JM, Kerr ND, Welz-Bosna M, Gallagher RM. Preliminary evaluation of the Health Background Questionnaire for Pain and clinical encounter form for pain. Pain Med. 2005;6:443-451.[Medline]
8. Herr K. Pain assessment in the older adult with verbal communication skills. In: Gibson SJ, Weiner DK, eds. Pain in Older Persons, Progress in Pain Research and Management. Vol 35. Seattle: IASP Press; 2005:111–133.
9. Helme RD, Gibson SJ. Measurement and management of pain in older people. Australas J Ageing. 1998;17:5-10.
10. Di Bari M, Virgillo A, Matteuzzi D, et al. Predictive validity of measures of comorbidity in older community dwellers: the Insufficienza Cardiaca negli Anziani Residenti a Dicomano Study. J Am Geriatr Soc. 2006;54:210-216.[Medline]
11. Rozzini R, Frisoni GB, Ferrucci L, et al. Geriatric Index of Comorbidity: validation and comparison with other measures of comorbidity. Age Ageing. 2002;31:277-285.[Abstract/Free Full Text]
12. Elixhauser A, Stiener C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36:8-27.[Medline]
13. Parmelee PA, Thuras PD, Katz IR, Lawton MP. Validation of the Cumulative Illness Rating Score in a geriatric residential population. J Am Geriatr Soc. 1995;43:130-137.[Medline]
14. Ghione S. Hypertension-associated hypalgesia. Evidence in experimental animals and humans, pathophysiological mechanisms and clinical consequences. Hypertension. 1996;28:494-504.[Abstract/Free Full Text]
15. Esposito AL. Community-acquired bacteremic pneumococcal pneumonia. Effect of age on manifestations and outcome. Arch Intern Med. 1984;144:945-948.[Abstract/Free Full Text]
16. Whelan CT, Jin L, Meltzer D. Pain and satisfaction with pain control in hospitalized medical patients: no such thing as low risk. Arch Intern Med. 2004;164:175-180.[Abstract/Free Full Text]
17. Farrell MJ, Gibson SJ, Helme RD. The effect of medical status and diagnosis on the activity of elderly pain clinic patients. J Am Geriatr Soc. 1995;43:102-107.[Medline]
18. Corran TM, Farrell MJ, Helme RD, Gibson SJ. The classification of patients with chronic pain: age as a contributing factor. Clin J Pain. 1997;13:207-214.[Medline]
19. Helme RD, Gibson SJ. Pain in the elderly. Prog Pain Res Manage. 1997;8:919-944.
20. Weiner DK, Rudy TE, Gaur S. Are all older adults with persistent pain created equal? Preliminary evidence of a multiaxial taxonomy. Pain Res Manag. 2001;6:133-141.[Medline]
21. Helme RD, Bradbeer M, Katz B, Gibson SJ. Management of chronic nonmalignant pain in the elderly: experience of an outpatient setting. In: Mostofsky DI, Lomranz J, eds. Handbook of Pain and Aging. New York: Plenum Press; 1997;241–266.
22. Linn BS, Linn MW, Gruel L. Cumulative Illness Rating Scale. J Am Geriatr Soc. 1968;16:622-626.[Medline]
23. Keller BK, Potter JF. Predictors of mortality in outpatient geriatric evaluation and management clinic patients. J Gerontol Med Sci. 1994;49A:M246-M251.
24. Yesavage TJ, Brink TG, Rose RL, Adrey M. The Geriatric Depression Rating Scale: comparison with other self-report and psychiatric rating scales. J Psychol Res. 1983;17:37-49.
25. Montorio I, Izal M. The Geriatric Depression Scale: a review of its development and utility. Int Psychogeriatr. 1996;8:103-112.[Medline]
26. Spielberger CD. Manual for the State-Trait Anxiety Inventory. Palo Alto: Consulting Psychologist Press; 1983.
27. Kvaal K, Laake K, Engedal K. Psychometric properties of the state part of the Spielberger State-Trait Anxiety Inventory (STAI) in geriatric patients. Int J Geriatr Psychiatry. 2001;16:980-986.[Medline]
28. Bergner M, Bobbitt RA, Carter WB, et al. The Sickness Impact Profile: development and final revision of a health status measure. Med Care. 1981;19:787-805.[Medline]
29. Fix AJ, Daughton DM. Human Activities Profile: Professional Manual. Odessa, FL: Psychological Assessment Resources Inc.; 1988.
30. Farrell MJ, Gibson SJ, Helme RD. Measuring the activity level of older people with chronic pain. Clin J Pain. 1996;12:6-12.[Medline]
31. Fried LP, Tangen CM, Walston J, et al. Cardiovascular Health Study Collaborative Research Group. Frailty in older adults: evidence for a phenotype. J Gerontol Med Sci. 2001;56A:M146-M156.[Abstract/Free Full Text]
32. Penninx BW, Beekman AT, Ormel J, et al. Psychological status among elderly people with chronic disease: does type of disease play a part? J Psychosom Res. 1996;40:521-534.[Medline]
33. Lyness JM, Duberstein PR, King DA, Cox C, Caine ED. Medical illness burden, trait neuroticism and depression in older primary care patients. Am J Psychiatry. 1998;155:969-971.[Abstract/Free Full Text]
34. Dunlop DD, Manheim LM, Sohn MW, Liu X, Chang RW. Incidence of functional limitation in older adults: the impact of gender, race and chronic conditions. Arch Phys Med Rehabil. 2002;83:964-971.[Medline]
35. Cho CY, Alessi CA, Cho M, et al. The association between chronic illness and functional change among participants in a comprehensive geriatric assessment program. J Am Geriatr Soc. 1988;46:677-682.

This Article Abstract Full Text (PDF) Services Download to citation manager PubMed PubMed Citation