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Living with disability: Patterns of health problems and symptom mediation of health consequences
Disability and Health Journal 5 (2012) 151e158 www.disabilityandhealthjnl.com
Research Papers
Living with disability: Patterns of health problems and symptom mediation of health consequences Brandon J. Patterson, Pharm.D.a,*, William R. Doucette, Ph.D.a, Scott D. Lindgren, Ph.D.b, and Elizabeth A. Chrischilles, Ph.D.c a
Department of Pharmacy Practice and Science, University of Iowa College of Pharmacy, Iowa City, IA b Department of Pediatrics, University of Iowa College of Medicine, Iowa City, IA c Department of Epidemiology, University of Iowa College of Public Health, Iowa City, IA
Abstract Background: People with disability experience a range of symptoms that may serve as an important linkage between disability and other health consequences. The aims of this study were to describe and compare symptom experiences of people with and without disability using a population-based sample and to test direct relationships between disability and health status and indirect effects of disability mediated through symptom experience. Methods: A Midwestern sample of 12,249 adults aged 40 and older responded to a cross-sectional survey. Data collected included symptom prevalence and frequencies for 21 commonly reported symptoms, self-perceived health status and physical functioning, number of medications, and demographic variables. Two mediation analyses were conducted using cumulative symptom frequency as the mediator between disability status and both self-rated health and physical functioning. Results: Adults with disability reported significantly greater prevalence and frequencies for all 21 symptoms, with pain and fatigue being the most common. The indirect effect through cumulative symptom frequency explained roughly half of the total effect of disability on general health status, and about one third of the total effect of disability on physical functioning. Conclusions: This study found evidence supporting the diverse and significant symptom experience of people living with disability, especially for symptoms of pain and fatigue. Moreover, symptom experience was found to partially mediate the effects of disability on self-reported general health status and physical functioning. This provides support for symptoms serving as an important link to health outcomes in patients with disability. Ó 2012 Elsevier Inc. All rights reserved. Keywords: Symptom; Disability; Physical function; Health status
Recent studies have demonstrated that disability results in $397.9 billion in healthcare costs in the United States, and patients with disability face 3.5 times higher healthcare costs The authors have no conflicts of interest to declare. This project was funded by grants from the Centers for Disease Control (1 R01 DD000107-01) and the Agency for Healthcare Research and Quality (1 U18 HS016094-01) led by E. A. Chrischilles. The opinions contained in this manuscript are those of the authors and do not necessarily reflect those of the Department of Health and Human Services. Notes: Mediation analyses made using Preacher and Hayes approach [24]. Effects of covariates are not shown in figure but described in text. Values on solid lines represent standardized regression coefficients of direct effects; values on dashed line represent standardized regression coefficients of indirect effect of disability status mediated through cumulative symptom frequency; R2 represent the fully mediated model including covariates; **p! .01. * Corresponding author: PHR S518, 115 S. Grand Avenue, Iowa City, IA 52242. E-mail address: [email protected] (B.J. Patterson). 1936-6574/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.dhjo.2012.03.001
than persons without disability [1]. Approximately one in five Americans have a disability, and projections indicate a significant increase in the number of persons with disability is likely to occur over the next decade [2,3]. Understanding complex relationships between disability and other health problems could have a substantial impact on understanding and improving the health of a significant proportion of the population and could help control healthcare costs. Scholars have long sought to understand the relationship between disability and other aspects of health. Nagi’s classic model of disablement defined how underlying pathologies can create impairments (including physiological, mental, or emotional abnormalities) and described how impairments can lead to physical limitations and subsequent disability [4]. Nagi’s model of disablement was further advanced by Verbrugge and Jette by including the effects of risk factors (such as demographic characteristics and environmental adaptations) on impairments, as well as the influences of accommodations and coping strategies on functional
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limitations [5]. For this model, disability is not a personal characteristic but is instead a gap between a person’s capabilities and environmental demands. In addition to expanding the disablement model, Verbrugge and Jette described instances where disability may contribute to secondary and associated comorbidities, such as new pathologies and commonly experienced symptoms [5]. Research focused specifically on symptom experience may provide further insights into the process of disablement and increase our ability to provide efficient care to persons with disability. The question, therefore, is how symptoms relate to the health and disability status of an individual. The Symptom Experience Model is one conceptual framework that describes how symptoms can relate to conditions or disabilities and to general health and functional status [6]. This model posits that the perception of symptoms, defined by their prevalence, frequency, and intensity, are preceded by antecedents, including an individual’s demographics and predisposing health characteristics. As symptoms manifest, patients experience resulting consequences that can include changes in mood, general health status, functional status, and overall survival. In this model, symptoms mediate between an individual’s current demographic and health characteristics and resultant health consequences. Testing the fit of symptoms as mediators can provide a deeper understanding of the health consequences associated with having a disability. Symptoms remain a poorly understood and significant problem in the U.S. health care system. Studies of the general population have consistently demonstrated symptoms as having a negative effect on health status even at minimal presence [7-10]. Prospective, longitudinal research has provided evidence to suggest that there is a causal relationship that links experiencing symptoms to having limitations in physical functioning [11,12]. In addition, symptoms are often not reported to healthcare providers even though they can have a profound influence on general health status [13-16]. It has been noted in the literature that people with disabilities should pay particular attention to symptoms, injuries, and other conditions to prevent further disablement [17,18]. What is not known is how symptoms fit into the disablement process, specifically the extent to which they mediate health outcomes when experienced by people with disabilities. The research aims of this cross-sectional study were to describe and compare the symptom experiences of people with and without disability using a population-based sample and test direct relationships between disability and health status and indirect effects of disability mediated through symptom experience. Guided by a conceptual model for symptom experience, we examined the extent to which symptom prevalence and frequency mediate the relationship between disability and health. Our group hypothesized that persons with disability would experience more symptoms more frequently than persons without disability and that symptom perception would be negatively associated with functional status and general health outcomes.
Methods Subjects An age-stratified sample of the general population aged 40 and over from three Iowa metropolitan areas was selected using a voter registry. Individuals aged 40-64 comprised 74% of the study sample, whereas those aged 65þ comprised 26% of the sample. Questionnaires were sent to 34,804 persons with 12,330 returned. All questionnaires were retained for analysis if one item was answered and the date of birth and sex matched voter registry source data. Of those returned, 12,249 were useable for analytical purposes, resulting in a 35.2% useable response rate for our analysis. Measures The questionnaire, reviewed by an external advisory panel of disability advocates and community workers, included 13 items measuring demographics and functional status, general health status, and disability status. Demographic information measured included date of birth, sex, and ethnicity. Questionnaire items measuring health and functional status were the general health status item and physical function scale from the SF-36 v.2. Two ‘‘disability’’ items were taken from the 2006 Behavioral Risk Factor Surveillance System (BRFSS) survey [19,20]. The two BRFSS items ask (1) whether the person is limited in any activities due to physical, mental, or emotional problems and (2) whether the individual uses any special equipment to assist in mobility or communication. Participants were also asked to provide the number of medications prescribed by a doctor that they have used in the past 2 weeks, as another measure of disease characteristics. In addition, the questionnaire measured symptom experience, by asking subjects to identify the frequency of 21 commonly reported symptoms (e.g., ‘‘Painful or aching joints,’’ ‘‘Breathing difficulties’’) that they had experienced in the previous 4 weeks, using response choices of ‘‘not at all,’’ ‘‘once or twice,’’ ‘‘a few times,’’ ‘‘fairly often,’’ or ‘‘very often.’’ These 21 common symptoms were adapted using the Secondary Condition Surveillance Instrument and informed by three previous studies [21-24]. From the previous instruments used to measure secondary conditions, we merged all items to represent a complete list of symptoms. We then excluded items that measured specific diagnoses and activity limitations from the existing measures, as these were measured separately on our questionnaire. Statistical analysis Simple descriptive analysis included the calculation of frequencies, means, standard deviations, and bivariate correlations for all measured variables where appropriate. To test hypothesis associated with the first research aim, symptom prevalence, and frequency for persons with disabilities were compared with persons without disabilities using c2 statistics. A variable to assess symptom prevalence
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over the prior 4-week period (categorized as 0 5 ‘‘not at all’’; 1 5 ‘‘some’’) was created by recoding the initial symptom ratings such that any of the four categories of having the symptom were counted as ‘‘some’’ symptom prevalence. Symptom frequency data using the 5-point frequency scales previously described were also analyzed. Also, the mean symptom frequency scores for each sample group and each symptom were computed. To test the mediation hypothesis associated with research aim two, the method of Preacher and Hayes [25] was used. This modeling approach uses bootstrapping to estimate the confidence interval of the indirect effect of the independent variables on the dependent variables, or in this case the effect of disability on health outcome that is mediated through cumulative symptom frequency, whereas controlling for covariates. For the analyses, two mediated regression models were calculated, one for each dependent health outcome variable: general health status and physical functioning score. Health status was measured as a single item on the questionnaire and contained five possible responses ranging from poor to excellent. Because such a large sample size was analyzed, the general health status variable was treated as a continuous variable. The functional status measure was the 10-item SF-36 physical function scaled as continuous, norm-based variable [20]. This procedure creates a distribution with a mean of 50 and a standard deviation of 10. In both models, cumulative symptom frequency was included as the mediator. The cumulative symptom frequency scores were calculated for each participant by summating the symptom frequency scores for all 21 symptoms (potential range: 0-84). The independent variable in both models was disability status. Having a disability was treated as a dichotomous variable determined by having answered ‘‘yes’’ to at least one of the two BRFSS disability status items. This approach to modeling disability has been used by Drum et al. [26]. Other variables included as covariates included number of medications, age, ethnicity, and sex. For our analysis, respondents were categorized into four age groups: 40-50, 51-60, 61-70, and 71þ years; dummy variables were created and the 40-50 age category was used as the reference group. In regard to general health status, four dummy variables were created for excellent, very good, good, and fair self-reported health status, whereas poor health served as the reference group. Ethnicity was a dichotomous variable with ‘‘of Latino origin’’ being the reference group. No other ethnicities were used as they were not significantly reported by respondents of the survey. Sex was a dichotomous variable with females serving as the reference group. All statistics were calculated using IBM SPSS Statistics, Version 19 [27].
Results Demographic data and health variables are presented in Table 1. Persons with reported disability represented slightly over a third of the sample (37.8%). Over half of
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Table 1 Demographic characteristics and selected health variables (n 5 12,249) Variable Freq (%) Mean (SD; range) Sex Male Female Age (y) 40-50 51-60 61-70 71þ Ethnicity Non-Hispanic Hispanic Health status Excellent Very good Good Fair Poor Disabilitya Number of medicationsb Cumulative symptom frequencyc Physical functioning scored
5247 (42.8) 7002 (57.2) 59.74 (12.52; 40-101) 3308 3880 2462 2599
(27.0) (31.7) (20.1) (21.2)
11,908 (96.8) 117 (0.4) 1524 4650 4279 1322 281 4628
(12.6) (38.6) (35.5) (11.0) (2.3) (37.8) 3.0 (3.6;0-88) 15.6 (13.1;0-84) 48.4 (10.7;15-57)
Freq, frequency; SD, standard deviation; percentages shown are for valid data. a Indicates either having to use special equipment because of a health problem or being limited because of physical, mental, or emotional problems. b Number of prescribed medications taken in the past 2 weeks. c Calculated as summated symptom frequencies for all 21 symptoms, range 084. d Physical functioning score is calculated as norm-based transformation.
the sample (57.2%) was female. The largest age groups in the sample were comprised of people aged 51 to 60 (31.7%) and 40 to 50 year olds (27.0%) with the remaining sample evenly split between persons aged 61 to 70 and those 71 years of age and older. A majority of the sample was non-Hispanic (96.8%), and roughly half had either excellent or very good health status. Although excellent or very good health was less common in persons with disabilities than in those without (24.7% versus 67.4%, p ! .01) a substantial number of respondents with disabilities reported health that was at least very good. The average number of prescriptions for people in the sample was approximately three. The average physical functioning score for the sample was 48.4; as this had been transformed into a norm-based score, our sample was slightly below the norm of 50. Four-week symptom prevalence, and differences between respondents with and without disability, are presented in Table 2. Symptoms experienced by greater than 50% of the entire sample included: pain in joints (71.4%), pain in muscles (66.0%), problems sleeping (61.8%), backache (60.2%), and fatigue or tiredness (52.4%) Symptom prevalence for respondents with disabilities was significantly greater ( p ! .01) than for those without disabilities for all 21 symptoms. A much larger percentage of persons with disability reported fatigue or tiredness (32.3% more),
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Table 2 Comparisons of symptom prevalence between respondents with and without disabilities Symptom prevalencea,f Total Symptom Respondents provided prevalencea with disabilities Symptom responses n (%)b n (%)c
Symptom prevalencea,f Respondents with no disabilities n (%)d
Differences in percentagese of symptom prevalencea
Fatigue or tiredness Dizziness Numbness or tingling Drowsiness Breathing difficulties Dry mouth Pain in joints Backache Confusion Pain in muscles Blurry vision Difficulty urinating or leakiness Appetite changes Skin problems Constipation Problems sleeping Stomach problems Sexual problems Changes in mood Diarrhea Headache
3027 1713 2301 2874 1101 1336 4647 3878 1105 4321 1169 1866 1022 1471 1806 4136 1171 1280 3116 2097 3586
32.3 31.3 27.9 27.9 27.2 25.7 25.3 24.0 22.4 22.3 20.8 20.7 19.9 19.2 19.2 18.8 17.8 17.1 16.9 15.4 5.9
12,096 12,096 12,086 12,138 12,109 12,119 12,071 12,155 12,100 12,012 12,064 12,089 12,116 12,076 12,136 12,117 12,135 11,437 12,082 12,110 12,069
6334 4169 4967 5887 3004 3318 8616 7319 2788 7927 2816 3938 2547 3225 3778 7490 2691 2740 5765 4067 6012
(52.4) (34.5) (41.1) (48.5) (24.8) (27.4) (71.4) (60.2) (23.0) (66.0) (23.3) (32.6) (21.0) (26.7) (31.1) (61.8) (22.2) (24.0) (47.7) (33.6) (49.8)
3307 2456 2666 3013 1903 1982 3696 3441 1683 3606 1647 2072 1525 1754 1972 3354 1520 1460 2649 1970 2426
(72.5) (54.0) (58.5) (65.9) (41.8) (43.4) (87.1) (75.2) (37.0) (79.9) (36.3) (45.5) (33.4) (38.7) (43.1) (73.5) (33.3) (34.8) (58.3) (43.2) (53.5)
(40.2) (22.7) (30.6) (38.0) (14.6) (17.7) (61.8) (51.2) (14.6) (57.6) (15.5) (24.8) (13.5) (19.5) (23.9) (54.7) (15.5) (17.7) (41.4) (27.8) (47.6)
a
Prevalence was based on recalled frequency of symptoms over the past 4 weeks. The number and percentage of the respondents reporting of symptoms of any frequency. b Percentages are based on provided responses from all respondents. c Percentages are based on provided responses from respondents with disabilities. d Percentages are based on provided responses from respondents with no disabilities. e Differences are reported as symptom prevalence percentages based on provided responses from respondents with disabilities minus symptom prevalence percentages based on provided responses from respondents with no disabilities. f p ! .01 for all comparisons; c2 analysis was performed to compare differences in symptom prevalence across respondents with and without disabilities.
dizziness (31.3% more), numbness or tingling (27.9% more), drowsiness (27.9% more), and breathing difficulties (27.2% more). Symptom frequencies and differences in mean frequency by disability status are presented in Table 3. All measured symptoms were reported significantly more frequently by individuals with disability when compared with those without ( p ! .01). For the entire sample, the mean symptom frequency score was less than two, indicating that on average each symptom was perceived less than ‘‘a few times’’ during the previous 4-week period. The four most frequently experienced symptoms for the entire sample were pain in joints, pain in muscles, backache, and problems sleeping. Differences that corresponded to a 1-point change in symptom frequency on a 5-point scale, between persons with and without disability occurred for the following symptoms: pain in joints (mean difference 1.29), pain in muscles (1.01), fatigue or tiredness (1.00), and backache (1.00). Bivariate relationships among the variables used in the mediation analysis are presented in Table 4. A positive statistically significant relationship exists between disability status and cumulative symptom frequency (0.49, p ! .01),
as well as health outcome measures (physical functioning score, 0.66, p ! .01, general health status, 0.48, p ! .01). Also, cumulative symptom frequency was significantly related to both physical functioning score (0.63, p ! .01) and general health status (0.61, p ! .01). According to bivariate relationships, people with older ages experience higher cumulative symptom frequency. A higher number of medications are positively associated with disability status, higher cumulative symptom frequency, and lower scores on both health outcome measures. Men experience fewer symptoms, take fewer medicines, and have higher physical functioning scores, although the correlations are not strong. Results of the mediation analysis are presented in Figure 1. Disability status was positively associated with cumulative symptom frequency (0.38, p ! .01). Cumulative symptom frequency had a significant and negative association on general health status (0.42, p ! .01) and physical functioning (0.34, p ! .01). Disability had a negative total effect on general health status of 0.35 ( p ! .01) with a direct effect of 0.19 ( p ! .01) and an indirect effect mediated through cumulative symptom frequency of 0.16 ( p ! .01). Disability had a negative total effect on physical functioning of 0.46 ( p ! .01)
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Table 3 Comparisons of symptom frequencies between respondents with and without disabilities Symptom frequencya,f Total Symptom Respondents with provided frequencya disabilities Symptom responses Meanb (SD) Meanc (SD)
Symptom frequencya,f Respondents with no disabilities Meand (SD)
Pain in joints Pain in muscles Fatigue or tiredness Backache Numbness or tingling Drowsiness Problems sleeping Breathing difficulties Dizziness Dry mouth Sexual problems Difficulty urinating or leakiness Skin problems Confusion Blurry vision Constipation Appetite changes Stomach problems Diarrhea Headache Changes in mood
1.23 0.99 0.69 0.93 0.55 0.60 1.07 0.23 0.32 0.31 0.41 0.48 0.36 0.21 0.25 0.38 0.20 0.23 0.41 0.70 0.89
12,071 12,012 12,096 12,155 12,086 12,138 12,117 12,109 12,096 12,119 11,437 12,089 12,076 12,100 12,064 12,136 12,116 12,135 12,110 12,069 12,082
1.71 1.37 1.07 1.30 0.87 0.89 1.34 0.50 0.59 0.55 0.64 0.70 0.55 0.40 0.42 0.55 0.36 0.37 0.55 0.79 0.82
(1.42) (1.29) (1.26) (1.37) (1.25) (1.12) (1.33) (1.02) (0.97) (1.05) (1.28) (1.17) (1.06) (0.85) (0.90) (0.97) (0.80) (0.81) (0.92) (0.99) (1.04)
2.52 2.00 1.69 1.93 1.41 1.36 1.79 0.95 1.04 0.96 1.02 1.06 0.86 0.70 0.71 0.83 0.62 0.61 0.77 0.95 1.12
(1.37) (1.39) (1.38) (1.49) (1.46) (1.26) (1.41) (1.33) (1.19) (1.30) (1.55) (1.37) (1.27) (1.09) (1.13) (1.17) (1.01) (1.01) (1.08) (1.11) (1.18)
(1.21) (1.06) (1.01) (1.13) (0.97) (0.90) (1.20) (0.64) (0.67) (0.76) (1.02) (0.97) (0.85) (0.58) (0.67) (0.79) (0.58) (0.61) (0.78) (0.89) (0.64)
Differences in meanse of symptom frequenciesa 1.29 1.01 1.00 1.00 0.86 0.76 0.72 0.72 0.72 0.65 0.61 0.58 0.50 0.49 0.46 0.45 0.42 0.38 0.36 0.25 0.23
Frequency was based on recalled frequency of symptoms over the past 4 weeks. Data were coded so 0 5 ‘‘Not at all’’; 1 5 ‘‘Once or twice’’; 2 5 ‘‘A few times’’; 3 5 ‘‘Fairly often’’; and, 4 5 ‘‘Very often’’. The means and standard deviations are reported. SD 5 standard deviation. b Means are based on provided responses from all respondents. c Means are based on provided responses from respondents with disabilities. d Means are based on provided responses from respondents with no disabilities. e Differences are reported as symptom frequency means based on provided responses from respondents with disabilities minus symptom frequency means based on provided responses from respondents with no disabilities. f p ! .01 for all comparisons; c2 analysis was performed to compare differences in symptom frequencies between respondents with and without disabilities. a
with a direct effect of 0.33 ( p ! .01) and an indirect effect mediated through cumulative symptom frequency of 0.13 ( p ! .01). Bootstrapped sampled estimates of indirect effects were consistent with estimates derived from all of the data. Bias corrected confidence intervals for indirect effects in both models were significant (0.14 to 0.17 for general health status; 0.12 to 0.14 for physical functioning).
Covariates controlled for in the mediation models were also significant. Number of medications had a significant negative association with general health status (0.21, p ! .01) and physical functioning (0.15, p ! .01). Age had a significant negative association with general health status (0.02, p ! .05) and physical functioning (0.20, p ! .01). Ethnicity was statistically significant with the non-Latino respondents reporting slightly better general
Table 4 Bivariate correlation matrix for mediation model Variable 1
2
3
4
5
6
7
1. 2. 3. 4. 5. 6. 7. 8.
0.14a 0.06a 0.45a 0.01 0.63a 0.61a
0.02b 0.34a 0.03a 0.41a 0.22a
0.05a 0.01 0.09a 0.02
0.01 0.52a 0.48a
0.00 0.02b
0.63a
Some disability Cumulative symptom frequency Age Sex (male) Number of medications Ethnicity Physical functioning score General health status
0.49a 0.22a 0.01 0.40a 0.00 0.66a 0.48a
Spearman’s rho and Pearson correlation coefficients presented where appropriate; max n 5 12,249 although n will vary for correlations based on missing data. a p ! .01. b p ! .05.
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Figure 1. Mediation analysis of the relations between disability status, cumulative symptom frequency, and selected health outcomes (general health status or physical functioning score) controlling for age, sex, ethnicity, and number of medications.
health status (0.02, p 5 .04) and physical functioning (0.01, p 5 .03). Men compared with women reported lower general health status (0.05, p ! .01) but higher physical functioning (0.05, p ! .01).
Discussion In this population-based, age-stratified random sample of adults from three Midwestern metropolitan areas, there was a high symptom burden for persons meeting a BRFSS definition of disability, and the reporting of symptoms was strongly associated with lower self-rated general health status and poorer self-reported physical function. People with disability had a much higher prevalence and frequency of symptoms, especially pain and fatigue, suggesting that symptom experience may substantially mediate the relationship between disability and healthdalthough not everyone with a disability reported having poor health. Mediation models provided evidence for partial mediation by symptoms between disability status and health status. Associations between health outcomes and medication use, age, sex, and ethnicity warrant further investigation. As expected, our study confirms that persons with disabilities experience more symptoms than persons without disability [17,22]. The most frequently reported symptoms were pain and fatigue. Our study reaffirmed previous findings that emphasize the importance of pain and fatigue as major symptoms in persons with disability, to the extent that these are often referred to as ‘‘disability symptoms’’ [28,29]. People with disability experience a wide range of symptoms that may in part be attributed to inactivity, overuse, or disuse syndromes. The resulting symptoms and signs occur across an array of body systems, including musculoskeletal, cardiovascular, skin, urinary and digestive, respiratory,
metabolism, and central nervous system [30,31]. Where this study makes significant additional contributions is through the testing of mediation hypotheses linking symptoms between an individual’s disability status and general health and physical functioning. These findings expand our understanding of complex symptom-disability relationships across important health factors. Thus, future research involving the effects of disability on health and functioning should include assessment of symptom experience. This study identified a significant negative association for number of medications with self-reported general health status and physical functioning, controlling for disability and demographics. Elderly patients are commonly prescribed medications to treat diseases and symptoms in hopes of alleviating comorbid functional limitations and disruptions to health [32,33]. However, these medications also can produce side effects that may limit normal physical functioning. In quantifying the effects of medications on health outcomes, an index has been created that has been used in measuring physical limitations induced by anticholinergic and other sedating medications [34]. Although directionality of medication effects in this study is not identifiable, the significance they have with self-reported health outcomes in patients is profound. Also, sex has been shown to weakly influence symptom reporting and self-reported health outcomes in previous studies. It has been shown that females tend to report higher symptom burden than men even after controlling for mental health comorbidities [35]. Although our finding was significant for sex, the extent of the relationship was weak. This result matches the analysis by Verbrugge that found that women often report lower general health status, but that this relationship disappears when factors such as lifestyle, roles, stress, socioeconomic status, and health attitudes are controlled [36]. Robustness of sex differences in
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symptom reporting is thus questionable, especially when controlling for known confounders. As other research has reported, our study confirmed that there were persons with disability who report having very good or excellent health [28]. Thus, disability by itself does not necessarily result in poor overall health status. This phenomenon has sometimes been called the ‘‘disability paradox,’’ which describes how persons may be able to successfully adjust to having a disability while maintaining good health and overall quality of life despite the presence of ongoing physical challenges [37]. Likewise, there are people who reported good and excellent health with many reported symptoms. The proposed notion of ‘‘balanced living’’ serves as a model describing maintenance of stable quality of life for a person with disability or coping, and this model could be enriched by integration of factors related to symptom experience [26,38]. There are limitations to this study that must be recognized. Even though this was a population-based sample, the overall survey response was relatively low (35.2%) and unknown selection factors may affect the generalizability of the findings. Another limitation of the study is the use of our definition of disability. Future research should explore the relationship of specific disability subtypes to comorbidities and complications [39]. In addition, being a cross-sectional survey, this study cannot explicitly measure causal relationships. However, because respondents were asked about current symptoms, it is likely that disability preceded or was concurrent to symptom reporting. Further research could use longitudinal designs to explore other potential consequences of symptom experience as influenced by disability status, such as disease progression, survival, and more direct measures of psychosocial adaptation. Finally, symptom experience was narrowly measured in this study as cumulative symptom frequency. Further research could explore how the dimension of symptom intensity relates to disability and health outcomes. Conclusion This study found evidence supporting the diverse and significant symptom experience of people living with disability, especially for symptoms of pain and fatigue. Moreover, symptom experience was found to partially mediate the effects of disability on self-reported general health status and physical functioning. This suggests that symptoms serve as an important link to health outcomes in persons with disability. Further understanding of symptom experience may identify useful approaches to improving quality of life in disability and to prevent complications and costs associated with the disablement process. Acknowledgments The authors wish to Brian M. Gryzlak, MSW, MA, for his project assistance in study design and manuscript preparation.
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[24] Gandhi TK, Weingart SN, Borus J, et al. Adverse drug events in ambulatory care. New Eng J Med. 2003;348:1556-1564. [25] Preacher KJ, Hayes AF. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods. 2008;40:879-891. [26] Drum CE, Horner-Johnson W, Krahn GL. Self-rated health and healthy days: examining the ‘‘disability paradox.’’ Disabil Health J. 2008;1:71-78. [27] IBM SPSS Statistics (Version 19.0, Release 19.0.0.1) [Computer Program]. Chicago: SPSS, 2010. [28] Antonak RF, Livneh H. Psychosocial adaptation to disability and its investigation among persons with multiple sclerosis. Soc Sci Med. 1995;40:1099-1108. [29] Verbrugee LM, Sevak P. Disability symptoms and the price of selfsufficiency. J Aging Health. 2004;16:688-722. [30] Marge M. Health promotion for persons with disabilities: moving beyond rehabilitation. Am J Health Promotion. 1988;2:29-44. [31] Ravesloot C, Seekins T, Walsh J. A structural analysis of secondary conditions experienced by people with physical disabilities. Rehab Psychol. 1997;42:3-16.
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Research Papers
Living with disability: Patterns of health problems and symptom mediation of health consequences Brandon J. Patterson, Pharm.D.a,*, William R. Doucette, Ph.D.a, Scott D. Lindgren, Ph.D.b, and Elizabeth A. Chrischilles, Ph.D.c a
Department of Pharmacy Practice and Science, University of Iowa College of Pharmacy, Iowa City, IA b Department of Pediatrics, University of Iowa College of Medicine, Iowa City, IA c Department of Epidemiology, University of Iowa College of Public Health, Iowa City, IA
Abstract Background: People with disability experience a range of symptoms that may serve as an important linkage between disability and other health consequences. The aims of this study were to describe and compare symptom experiences of people with and without disability using a population-based sample and to test direct relationships between disability and health status and indirect effects of disability mediated through symptom experience. Methods: A Midwestern sample of 12,249 adults aged 40 and older responded to a cross-sectional survey. Data collected included symptom prevalence and frequencies for 21 commonly reported symptoms, self-perceived health status and physical functioning, number of medications, and demographic variables. Two mediation analyses were conducted using cumulative symptom frequency as the mediator between disability status and both self-rated health and physical functioning. Results: Adults with disability reported significantly greater prevalence and frequencies for all 21 symptoms, with pain and fatigue being the most common. The indirect effect through cumulative symptom frequency explained roughly half of the total effect of disability on general health status, and about one third of the total effect of disability on physical functioning. Conclusions: This study found evidence supporting the diverse and significant symptom experience of people living with disability, especially for symptoms of pain and fatigue. Moreover, symptom experience was found to partially mediate the effects of disability on self-reported general health status and physical functioning. This provides support for symptoms serving as an important link to health outcomes in patients with disability. Ó 2012 Elsevier Inc. All rights reserved. Keywords: Symptom; Disability; Physical function; Health status
Recent studies have demonstrated that disability results in $397.9 billion in healthcare costs in the United States, and patients with disability face 3.5 times higher healthcare costs The authors have no conflicts of interest to declare. This project was funded by grants from the Centers for Disease Control (1 R01 DD000107-01) and the Agency for Healthcare Research and Quality (1 U18 HS016094-01) led by E. A. Chrischilles. The opinions contained in this manuscript are those of the authors and do not necessarily reflect those of the Department of Health and Human Services. Notes: Mediation analyses made using Preacher and Hayes approach [24]. Effects of covariates are not shown in figure but described in text. Values on solid lines represent standardized regression coefficients of direct effects; values on dashed line represent standardized regression coefficients of indirect effect of disability status mediated through cumulative symptom frequency; R2 represent the fully mediated model including covariates; **p! .01. * Corresponding author: PHR S518, 115 S. Grand Avenue, Iowa City, IA 52242. E-mail address: [email protected] (B.J. Patterson). 1936-6574/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.dhjo.2012.03.001
than persons without disability [1]. Approximately one in five Americans have a disability, and projections indicate a significant increase in the number of persons with disability is likely to occur over the next decade [2,3]. Understanding complex relationships between disability and other health problems could have a substantial impact on understanding and improving the health of a significant proportion of the population and could help control healthcare costs. Scholars have long sought to understand the relationship between disability and other aspects of health. Nagi’s classic model of disablement defined how underlying pathologies can create impairments (including physiological, mental, or emotional abnormalities) and described how impairments can lead to physical limitations and subsequent disability [4]. Nagi’s model of disablement was further advanced by Verbrugge and Jette by including the effects of risk factors (such as demographic characteristics and environmental adaptations) on impairments, as well as the influences of accommodations and coping strategies on functional
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limitations [5]. For this model, disability is not a personal characteristic but is instead a gap between a person’s capabilities and environmental demands. In addition to expanding the disablement model, Verbrugge and Jette described instances where disability may contribute to secondary and associated comorbidities, such as new pathologies and commonly experienced symptoms [5]. Research focused specifically on symptom experience may provide further insights into the process of disablement and increase our ability to provide efficient care to persons with disability. The question, therefore, is how symptoms relate to the health and disability status of an individual. The Symptom Experience Model is one conceptual framework that describes how symptoms can relate to conditions or disabilities and to general health and functional status [6]. This model posits that the perception of symptoms, defined by their prevalence, frequency, and intensity, are preceded by antecedents, including an individual’s demographics and predisposing health characteristics. As symptoms manifest, patients experience resulting consequences that can include changes in mood, general health status, functional status, and overall survival. In this model, symptoms mediate between an individual’s current demographic and health characteristics and resultant health consequences. Testing the fit of symptoms as mediators can provide a deeper understanding of the health consequences associated with having a disability. Symptoms remain a poorly understood and significant problem in the U.S. health care system. Studies of the general population have consistently demonstrated symptoms as having a negative effect on health status even at minimal presence [7-10]. Prospective, longitudinal research has provided evidence to suggest that there is a causal relationship that links experiencing symptoms to having limitations in physical functioning [11,12]. In addition, symptoms are often not reported to healthcare providers even though they can have a profound influence on general health status [13-16]. It has been noted in the literature that people with disabilities should pay particular attention to symptoms, injuries, and other conditions to prevent further disablement [17,18]. What is not known is how symptoms fit into the disablement process, specifically the extent to which they mediate health outcomes when experienced by people with disabilities. The research aims of this cross-sectional study were to describe and compare the symptom experiences of people with and without disability using a population-based sample and test direct relationships between disability and health status and indirect effects of disability mediated through symptom experience. Guided by a conceptual model for symptom experience, we examined the extent to which symptom prevalence and frequency mediate the relationship between disability and health. Our group hypothesized that persons with disability would experience more symptoms more frequently than persons without disability and that symptom perception would be negatively associated with functional status and general health outcomes.
Methods Subjects An age-stratified sample of the general population aged 40 and over from three Iowa metropolitan areas was selected using a voter registry. Individuals aged 40-64 comprised 74% of the study sample, whereas those aged 65þ comprised 26% of the sample. Questionnaires were sent to 34,804 persons with 12,330 returned. All questionnaires were retained for analysis if one item was answered and the date of birth and sex matched voter registry source data. Of those returned, 12,249 were useable for analytical purposes, resulting in a 35.2% useable response rate for our analysis. Measures The questionnaire, reviewed by an external advisory panel of disability advocates and community workers, included 13 items measuring demographics and functional status, general health status, and disability status. Demographic information measured included date of birth, sex, and ethnicity. Questionnaire items measuring health and functional status were the general health status item and physical function scale from the SF-36 v.2. Two ‘‘disability’’ items were taken from the 2006 Behavioral Risk Factor Surveillance System (BRFSS) survey [19,20]. The two BRFSS items ask (1) whether the person is limited in any activities due to physical, mental, or emotional problems and (2) whether the individual uses any special equipment to assist in mobility or communication. Participants were also asked to provide the number of medications prescribed by a doctor that they have used in the past 2 weeks, as another measure of disease characteristics. In addition, the questionnaire measured symptom experience, by asking subjects to identify the frequency of 21 commonly reported symptoms (e.g., ‘‘Painful or aching joints,’’ ‘‘Breathing difficulties’’) that they had experienced in the previous 4 weeks, using response choices of ‘‘not at all,’’ ‘‘once or twice,’’ ‘‘a few times,’’ ‘‘fairly often,’’ or ‘‘very often.’’ These 21 common symptoms were adapted using the Secondary Condition Surveillance Instrument and informed by three previous studies [21-24]. From the previous instruments used to measure secondary conditions, we merged all items to represent a complete list of symptoms. We then excluded items that measured specific diagnoses and activity limitations from the existing measures, as these were measured separately on our questionnaire. Statistical analysis Simple descriptive analysis included the calculation of frequencies, means, standard deviations, and bivariate correlations for all measured variables where appropriate. To test hypothesis associated with the first research aim, symptom prevalence, and frequency for persons with disabilities were compared with persons without disabilities using c2 statistics. A variable to assess symptom prevalence
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over the prior 4-week period (categorized as 0 5 ‘‘not at all’’; 1 5 ‘‘some’’) was created by recoding the initial symptom ratings such that any of the four categories of having the symptom were counted as ‘‘some’’ symptom prevalence. Symptom frequency data using the 5-point frequency scales previously described were also analyzed. Also, the mean symptom frequency scores for each sample group and each symptom were computed. To test the mediation hypothesis associated with research aim two, the method of Preacher and Hayes [25] was used. This modeling approach uses bootstrapping to estimate the confidence interval of the indirect effect of the independent variables on the dependent variables, or in this case the effect of disability on health outcome that is mediated through cumulative symptom frequency, whereas controlling for covariates. For the analyses, two mediated regression models were calculated, one for each dependent health outcome variable: general health status and physical functioning score. Health status was measured as a single item on the questionnaire and contained five possible responses ranging from poor to excellent. Because such a large sample size was analyzed, the general health status variable was treated as a continuous variable. The functional status measure was the 10-item SF-36 physical function scaled as continuous, norm-based variable [20]. This procedure creates a distribution with a mean of 50 and a standard deviation of 10. In both models, cumulative symptom frequency was included as the mediator. The cumulative symptom frequency scores were calculated for each participant by summating the symptom frequency scores for all 21 symptoms (potential range: 0-84). The independent variable in both models was disability status. Having a disability was treated as a dichotomous variable determined by having answered ‘‘yes’’ to at least one of the two BRFSS disability status items. This approach to modeling disability has been used by Drum et al. [26]. Other variables included as covariates included number of medications, age, ethnicity, and sex. For our analysis, respondents were categorized into four age groups: 40-50, 51-60, 61-70, and 71þ years; dummy variables were created and the 40-50 age category was used as the reference group. In regard to general health status, four dummy variables were created for excellent, very good, good, and fair self-reported health status, whereas poor health served as the reference group. Ethnicity was a dichotomous variable with ‘‘of Latino origin’’ being the reference group. No other ethnicities were used as they were not significantly reported by respondents of the survey. Sex was a dichotomous variable with females serving as the reference group. All statistics were calculated using IBM SPSS Statistics, Version 19 [27].
Results Demographic data and health variables are presented in Table 1. Persons with reported disability represented slightly over a third of the sample (37.8%). Over half of
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Table 1 Demographic characteristics and selected health variables (n 5 12,249) Variable Freq (%) Mean (SD; range) Sex Male Female Age (y) 40-50 51-60 61-70 71þ Ethnicity Non-Hispanic Hispanic Health status Excellent Very good Good Fair Poor Disabilitya Number of medicationsb Cumulative symptom frequencyc Physical functioning scored
5247 (42.8) 7002 (57.2) 59.74 (12.52; 40-101) 3308 3880 2462 2599
(27.0) (31.7) (20.1) (21.2)
11,908 (96.8) 117 (0.4) 1524 4650 4279 1322 281 4628
(12.6) (38.6) (35.5) (11.0) (2.3) (37.8) 3.0 (3.6;0-88) 15.6 (13.1;0-84) 48.4 (10.7;15-57)
Freq, frequency; SD, standard deviation; percentages shown are for valid data. a Indicates either having to use special equipment because of a health problem or being limited because of physical, mental, or emotional problems. b Number of prescribed medications taken in the past 2 weeks. c Calculated as summated symptom frequencies for all 21 symptoms, range 084. d Physical functioning score is calculated as norm-based transformation.
the sample (57.2%) was female. The largest age groups in the sample were comprised of people aged 51 to 60 (31.7%) and 40 to 50 year olds (27.0%) with the remaining sample evenly split between persons aged 61 to 70 and those 71 years of age and older. A majority of the sample was non-Hispanic (96.8%), and roughly half had either excellent or very good health status. Although excellent or very good health was less common in persons with disabilities than in those without (24.7% versus 67.4%, p ! .01) a substantial number of respondents with disabilities reported health that was at least very good. The average number of prescriptions for people in the sample was approximately three. The average physical functioning score for the sample was 48.4; as this had been transformed into a norm-based score, our sample was slightly below the norm of 50. Four-week symptom prevalence, and differences between respondents with and without disability, are presented in Table 2. Symptoms experienced by greater than 50% of the entire sample included: pain in joints (71.4%), pain in muscles (66.0%), problems sleeping (61.8%), backache (60.2%), and fatigue or tiredness (52.4%) Symptom prevalence for respondents with disabilities was significantly greater ( p ! .01) than for those without disabilities for all 21 symptoms. A much larger percentage of persons with disability reported fatigue or tiredness (32.3% more),
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Table 2 Comparisons of symptom prevalence between respondents with and without disabilities Symptom prevalencea,f Total Symptom Respondents provided prevalencea with disabilities Symptom responses n (%)b n (%)c
Symptom prevalencea,f Respondents with no disabilities n (%)d
Differences in percentagese of symptom prevalencea
Fatigue or tiredness Dizziness Numbness or tingling Drowsiness Breathing difficulties Dry mouth Pain in joints Backache Confusion Pain in muscles Blurry vision Difficulty urinating or leakiness Appetite changes Skin problems Constipation Problems sleeping Stomach problems Sexual problems Changes in mood Diarrhea Headache
3027 1713 2301 2874 1101 1336 4647 3878 1105 4321 1169 1866 1022 1471 1806 4136 1171 1280 3116 2097 3586
32.3 31.3 27.9 27.9 27.2 25.7 25.3 24.0 22.4 22.3 20.8 20.7 19.9 19.2 19.2 18.8 17.8 17.1 16.9 15.4 5.9
12,096 12,096 12,086 12,138 12,109 12,119 12,071 12,155 12,100 12,012 12,064 12,089 12,116 12,076 12,136 12,117 12,135 11,437 12,082 12,110 12,069
6334 4169 4967 5887 3004 3318 8616 7319 2788 7927 2816 3938 2547 3225 3778 7490 2691 2740 5765 4067 6012
(52.4) (34.5) (41.1) (48.5) (24.8) (27.4) (71.4) (60.2) (23.0) (66.0) (23.3) (32.6) (21.0) (26.7) (31.1) (61.8) (22.2) (24.0) (47.7) (33.6) (49.8)
3307 2456 2666 3013 1903 1982 3696 3441 1683 3606 1647 2072 1525 1754 1972 3354 1520 1460 2649 1970 2426
(72.5) (54.0) (58.5) (65.9) (41.8) (43.4) (87.1) (75.2) (37.0) (79.9) (36.3) (45.5) (33.4) (38.7) (43.1) (73.5) (33.3) (34.8) (58.3) (43.2) (53.5)
(40.2) (22.7) (30.6) (38.0) (14.6) (17.7) (61.8) (51.2) (14.6) (57.6) (15.5) (24.8) (13.5) (19.5) (23.9) (54.7) (15.5) (17.7) (41.4) (27.8) (47.6)
a
Prevalence was based on recalled frequency of symptoms over the past 4 weeks. The number and percentage of the respondents reporting of symptoms of any frequency. b Percentages are based on provided responses from all respondents. c Percentages are based on provided responses from respondents with disabilities. d Percentages are based on provided responses from respondents with no disabilities. e Differences are reported as symptom prevalence percentages based on provided responses from respondents with disabilities minus symptom prevalence percentages based on provided responses from respondents with no disabilities. f p ! .01 for all comparisons; c2 analysis was performed to compare differences in symptom prevalence across respondents with and without disabilities.
dizziness (31.3% more), numbness or tingling (27.9% more), drowsiness (27.9% more), and breathing difficulties (27.2% more). Symptom frequencies and differences in mean frequency by disability status are presented in Table 3. All measured symptoms were reported significantly more frequently by individuals with disability when compared with those without ( p ! .01). For the entire sample, the mean symptom frequency score was less than two, indicating that on average each symptom was perceived less than ‘‘a few times’’ during the previous 4-week period. The four most frequently experienced symptoms for the entire sample were pain in joints, pain in muscles, backache, and problems sleeping. Differences that corresponded to a 1-point change in symptom frequency on a 5-point scale, between persons with and without disability occurred for the following symptoms: pain in joints (mean difference 1.29), pain in muscles (1.01), fatigue or tiredness (1.00), and backache (1.00). Bivariate relationships among the variables used in the mediation analysis are presented in Table 4. A positive statistically significant relationship exists between disability status and cumulative symptom frequency (0.49, p ! .01),
as well as health outcome measures (physical functioning score, 0.66, p ! .01, general health status, 0.48, p ! .01). Also, cumulative symptom frequency was significantly related to both physical functioning score (0.63, p ! .01) and general health status (0.61, p ! .01). According to bivariate relationships, people with older ages experience higher cumulative symptom frequency. A higher number of medications are positively associated with disability status, higher cumulative symptom frequency, and lower scores on both health outcome measures. Men experience fewer symptoms, take fewer medicines, and have higher physical functioning scores, although the correlations are not strong. Results of the mediation analysis are presented in Figure 1. Disability status was positively associated with cumulative symptom frequency (0.38, p ! .01). Cumulative symptom frequency had a significant and negative association on general health status (0.42, p ! .01) and physical functioning (0.34, p ! .01). Disability had a negative total effect on general health status of 0.35 ( p ! .01) with a direct effect of 0.19 ( p ! .01) and an indirect effect mediated through cumulative symptom frequency of 0.16 ( p ! .01). Disability had a negative total effect on physical functioning of 0.46 ( p ! .01)
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Table 3 Comparisons of symptom frequencies between respondents with and without disabilities Symptom frequencya,f Total Symptom Respondents with provided frequencya disabilities Symptom responses Meanb (SD) Meanc (SD)
Symptom frequencya,f Respondents with no disabilities Meand (SD)
Pain in joints Pain in muscles Fatigue or tiredness Backache Numbness or tingling Drowsiness Problems sleeping Breathing difficulties Dizziness Dry mouth Sexual problems Difficulty urinating or leakiness Skin problems Confusion Blurry vision Constipation Appetite changes Stomach problems Diarrhea Headache Changes in mood
1.23 0.99 0.69 0.93 0.55 0.60 1.07 0.23 0.32 0.31 0.41 0.48 0.36 0.21 0.25 0.38 0.20 0.23 0.41 0.70 0.89
12,071 12,012 12,096 12,155 12,086 12,138 12,117 12,109 12,096 12,119 11,437 12,089 12,076 12,100 12,064 12,136 12,116 12,135 12,110 12,069 12,082
1.71 1.37 1.07 1.30 0.87 0.89 1.34 0.50 0.59 0.55 0.64 0.70 0.55 0.40 0.42 0.55 0.36 0.37 0.55 0.79 0.82
(1.42) (1.29) (1.26) (1.37) (1.25) (1.12) (1.33) (1.02) (0.97) (1.05) (1.28) (1.17) (1.06) (0.85) (0.90) (0.97) (0.80) (0.81) (0.92) (0.99) (1.04)
2.52 2.00 1.69 1.93 1.41 1.36 1.79 0.95 1.04 0.96 1.02 1.06 0.86 0.70 0.71 0.83 0.62 0.61 0.77 0.95 1.12
(1.37) (1.39) (1.38) (1.49) (1.46) (1.26) (1.41) (1.33) (1.19) (1.30) (1.55) (1.37) (1.27) (1.09) (1.13) (1.17) (1.01) (1.01) (1.08) (1.11) (1.18)
(1.21) (1.06) (1.01) (1.13) (0.97) (0.90) (1.20) (0.64) (0.67) (0.76) (1.02) (0.97) (0.85) (0.58) (0.67) (0.79) (0.58) (0.61) (0.78) (0.89) (0.64)
Differences in meanse of symptom frequenciesa 1.29 1.01 1.00 1.00 0.86 0.76 0.72 0.72 0.72 0.65 0.61 0.58 0.50 0.49 0.46 0.45 0.42 0.38 0.36 0.25 0.23
Frequency was based on recalled frequency of symptoms over the past 4 weeks. Data were coded so 0 5 ‘‘Not at all’’; 1 5 ‘‘Once or twice’’; 2 5 ‘‘A few times’’; 3 5 ‘‘Fairly often’’; and, 4 5 ‘‘Very often’’. The means and standard deviations are reported. SD 5 standard deviation. b Means are based on provided responses from all respondents. c Means are based on provided responses from respondents with disabilities. d Means are based on provided responses from respondents with no disabilities. e Differences are reported as symptom frequency means based on provided responses from respondents with disabilities minus symptom frequency means based on provided responses from respondents with no disabilities. f p ! .01 for all comparisons; c2 analysis was performed to compare differences in symptom frequencies between respondents with and without disabilities. a
with a direct effect of 0.33 ( p ! .01) and an indirect effect mediated through cumulative symptom frequency of 0.13 ( p ! .01). Bootstrapped sampled estimates of indirect effects were consistent with estimates derived from all of the data. Bias corrected confidence intervals for indirect effects in both models were significant (0.14 to 0.17 for general health status; 0.12 to 0.14 for physical functioning).
Covariates controlled for in the mediation models were also significant. Number of medications had a significant negative association with general health status (0.21, p ! .01) and physical functioning (0.15, p ! .01). Age had a significant negative association with general health status (0.02, p ! .05) and physical functioning (0.20, p ! .01). Ethnicity was statistically significant with the non-Latino respondents reporting slightly better general
Table 4 Bivariate correlation matrix for mediation model Variable 1
2
3
4
5
6
7
1. 2. 3. 4. 5. 6. 7. 8.
0.14a 0.06a 0.45a 0.01 0.63a 0.61a
0.02b 0.34a 0.03a 0.41a 0.22a
0.05a 0.01 0.09a 0.02
0.01 0.52a 0.48a
0.00 0.02b
0.63a
Some disability Cumulative symptom frequency Age Sex (male) Number of medications Ethnicity Physical functioning score General health status
0.49a 0.22a 0.01 0.40a 0.00 0.66a 0.48a
Spearman’s rho and Pearson correlation coefficients presented where appropriate; max n 5 12,249 although n will vary for correlations based on missing data. a p ! .01. b p ! .05.
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Figure 1. Mediation analysis of the relations between disability status, cumulative symptom frequency, and selected health outcomes (general health status or physical functioning score) controlling for age, sex, ethnicity, and number of medications.
health status (0.02, p 5 .04) and physical functioning (0.01, p 5 .03). Men compared with women reported lower general health status (0.05, p ! .01) but higher physical functioning (0.05, p ! .01).
Discussion In this population-based, age-stratified random sample of adults from three Midwestern metropolitan areas, there was a high symptom burden for persons meeting a BRFSS definition of disability, and the reporting of symptoms was strongly associated with lower self-rated general health status and poorer self-reported physical function. People with disability had a much higher prevalence and frequency of symptoms, especially pain and fatigue, suggesting that symptom experience may substantially mediate the relationship between disability and healthdalthough not everyone with a disability reported having poor health. Mediation models provided evidence for partial mediation by symptoms between disability status and health status. Associations between health outcomes and medication use, age, sex, and ethnicity warrant further investigation. As expected, our study confirms that persons with disabilities experience more symptoms than persons without disability [17,22]. The most frequently reported symptoms were pain and fatigue. Our study reaffirmed previous findings that emphasize the importance of pain and fatigue as major symptoms in persons with disability, to the extent that these are often referred to as ‘‘disability symptoms’’ [28,29]. People with disability experience a wide range of symptoms that may in part be attributed to inactivity, overuse, or disuse syndromes. The resulting symptoms and signs occur across an array of body systems, including musculoskeletal, cardiovascular, skin, urinary and digestive, respiratory,
metabolism, and central nervous system [30,31]. Where this study makes significant additional contributions is through the testing of mediation hypotheses linking symptoms between an individual’s disability status and general health and physical functioning. These findings expand our understanding of complex symptom-disability relationships across important health factors. Thus, future research involving the effects of disability on health and functioning should include assessment of symptom experience. This study identified a significant negative association for number of medications with self-reported general health status and physical functioning, controlling for disability and demographics. Elderly patients are commonly prescribed medications to treat diseases and symptoms in hopes of alleviating comorbid functional limitations and disruptions to health [32,33]. However, these medications also can produce side effects that may limit normal physical functioning. In quantifying the effects of medications on health outcomes, an index has been created that has been used in measuring physical limitations induced by anticholinergic and other sedating medications [34]. Although directionality of medication effects in this study is not identifiable, the significance they have with self-reported health outcomes in patients is profound. Also, sex has been shown to weakly influence symptom reporting and self-reported health outcomes in previous studies. It has been shown that females tend to report higher symptom burden than men even after controlling for mental health comorbidities [35]. Although our finding was significant for sex, the extent of the relationship was weak. This result matches the analysis by Verbrugge that found that women often report lower general health status, but that this relationship disappears when factors such as lifestyle, roles, stress, socioeconomic status, and health attitudes are controlled [36]. Robustness of sex differences in
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symptom reporting is thus questionable, especially when controlling for known confounders. As other research has reported, our study confirmed that there were persons with disability who report having very good or excellent health [28]. Thus, disability by itself does not necessarily result in poor overall health status. This phenomenon has sometimes been called the ‘‘disability paradox,’’ which describes how persons may be able to successfully adjust to having a disability while maintaining good health and overall quality of life despite the presence of ongoing physical challenges [37]. Likewise, there are people who reported good and excellent health with many reported symptoms. The proposed notion of ‘‘balanced living’’ serves as a model describing maintenance of stable quality of life for a person with disability or coping, and this model could be enriched by integration of factors related to symptom experience [26,38]. There are limitations to this study that must be recognized. Even though this was a population-based sample, the overall survey response was relatively low (35.2%) and unknown selection factors may affect the generalizability of the findings. Another limitation of the study is the use of our definition of disability. Future research should explore the relationship of specific disability subtypes to comorbidities and complications [39]. In addition, being a cross-sectional survey, this study cannot explicitly measure causal relationships. However, because respondents were asked about current symptoms, it is likely that disability preceded or was concurrent to symptom reporting. Further research could use longitudinal designs to explore other potential consequences of symptom experience as influenced by disability status, such as disease progression, survival, and more direct measures of psychosocial adaptation. Finally, symptom experience was narrowly measured in this study as cumulative symptom frequency. Further research could explore how the dimension of symptom intensity relates to disability and health outcomes. Conclusion This study found evidence supporting the diverse and significant symptom experience of people living with disability, especially for symptoms of pain and fatigue. Moreover, symptom experience was found to partially mediate the effects of disability on self-reported general health status and physical functioning. This suggests that symptoms serve as an important link to health outcomes in persons with disability. Further understanding of symptom experience may identify useful approaches to improving quality of life in disability and to prevent complications and costs associated with the disablement process. Acknowledgments The authors wish to Brian M. Gryzlak, MSW, MA, for his project assistance in study design and manuscript preparation.
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