The major contribution of this article is the application of a novel approach to the estimation of the effects of individual conditions in the presence of comorbidity. The total number of disability days associated with the conditions considered herein is staggering. Over a 1-year period, each of the 53.4% of US adults with 1 or more of these conditions is estimated to average more than 1 full month (32.1 days) of health-related role disability, equivalent to nearly 3.6 billion days out of role in the population. Such large effects demand consideration in determining priorities in health care treatment and research.
Although several previous studies have incorporated the effects of comorbidity into estimates of the effects of specific conditions on a range of indirect outcomes (eg, days out of role, quality of life, various scales of role functioning),8,13,15,16,36
to our knowledge no prior study of a population-based sample has provided estimates of condition-specific disability for a range of physical and mental disorders, controlling for associations within and between classes of comorbid disorders. Our finding that the estimated condition-specific effects of virtually all conditions decreased after accounting for comorbidity suggests that prior studies have overestimated disease-specific effects on disability. However, there is a wide range of differences in the effects of comorbidity for the conditions that we studied. For instance, whereas the estimated effects of cancer and chronic obstructive pulmonary disease only decreased by 16%, the estimated effect of arthritis decreased by 69% in the models that incorporated comorbidity.
Musculoskeletal conditions and depression had the largest estimated effects on disability of all the conditions considered herein at both the individual and population levels. In light of the variability in methods of prior studies, it is striking that previous studies have also ranked musculoskeletal disorders and major depression as the conditions associated with the largest number of disability days at both the individual26,37
and population levels.15,38
Our results suggest that these conditions should be prioritized in the allocation of health care resources. A vivid illustration of the mismatch between health care resources and disease impact is provided by Druss et al,39
who found that musculoskeletal disorders and depression have the lowest health care expenditures relative to disability of any commonly occurring conditions in the United States.
Discrepancies between population-level and individual-level estimated effects of specific conditions are primarily attributable to variations in population prevalence estimates. For example, although arthritis is estimated to have a low individual-level effect on role disability, it has the third largest estimated effect at the population level because of its high prevalence. In contrast, low-prevalence, high-impact conditions, such as cancer, have low estimated population-level effects. Finally, a number of conditions known to have major public health effects, such as diabetes and hypertension, were not included in the final models because our simulation evaluated the incremental effects of specific conditions net of the effects of other conditions and found these incremental effects to be statistically insignificant. This is presumably because the effects of diabetes and hypertension are realized largely through progression to other conditions included in our analyses (eg, cardiovascular disorder, visual impairment).
Our results confirm those of several other studies in suggesting that the individual-level effects of mental conditions are as large as those of most chronic physical conditions.13,14,36,40
We found that the number of disability days associated with all mental conditions at the population level equals more than half (54%) the number of days associated with all the physical conditions considered herein at the population level. This demonstrates the enormous significance of mental conditions to overall illness-related disability. The substantial impact of mental disorders can be attributed to their high prevalence, substantial comorbidity with physical conditions, comparatively early age at onset, and broad influence on functional impairment.
Evidence of the relative effects of different chronic conditions on role disability may be of particular interest to employers,41–43
who have been at the forefront of efforts to develop targeted health care interventions to decrease workplace disability associated with chronic conditions.44–46
Evidence is mounting that such programs can have positive return on investment when effective treatments are available.47,48
Replication of our study among employed people could help to fill the gap in empirical data to guide resource allocation decisions for health-related research. Current data on health care costs that are based primarily on prevalence, mortality, and direct health care costs of chronic diseases are only beginning to include the substantial magnitude of indirect costs due to disability, absenteeism, and lower work productivity.9
The National Institutes of Health has recently established a program to evaluate the entire agency research portfolio to ensure that their research addresses urgent public health needs.49
Evidence on the comparative human and financial costs of chronic conditions should have a central role in this new evidence-based system of research priority setting.
Our findings should be considered in the context of 4 broad classes of limitations. The first class concerns measurement errors. Although CIDI diagnoses of DSM-IV
mental disorders have good concordance with independent clinical evaluations, 50,51
the checklist used to assess physical conditions was more superficial, possibly leading to underestimation of the prevalence or associations with disability of physical relative to mental conditions. However, the prevalence estimates obtained herein are similar to those in previous epidemiologic studies of physical conditions.25
The inclusion of acute conditions may have led to a greater increase in the estimated importance of physical relative to mental conditions because the most common acute conditions are physical (seasonal allergies, cold/flu, and strains/sprains).
Measurement errors also have to be considered in the outcome measure, days of role disability. Although this is the most widely used indicator of disability in the literature, recent research shows that reduced role performance on days in role also has an important effect on role disability.9,52,53
The relative effects of the conditions considered herein on reduced quantity or quality of role performance might be different from their effects on days out of role. Reports about days of role disability might also be biased by a combination of recall failure, which leads to underestimation, and “telescoping,” the tendency to recall events as occurring more recently than they actually occurred, 54
which leads to overestimation. Although previous research has shown that reports of work-loss days based on the disability questions used herein are unbiased in comparison with payroll records,21
no comparable objective measures exist to validate reports about disability on nonwork days or among people who are not employed.
The second limitation is that the different periods of measurement of disorders (12-month recall) and disability (30-day recall) could have introduced bias into the results even though our correction method leads to unbiased estimates if the profile of disability days in the 30 days before interview is typical of the profile across all months of the past year. Evidence that these profiles might not be entirely typical comes from methodological research showing that some respondents postpone participation in surveys when they have acute flare-ups of chronic conditions.55
As a result, respondents tend to be in somewhat better health during the month of interviews than during other months, causing the number of disability days in the 30 days before interview to be lower than in a typical month and creating somewhat conservative disability prevalence estimates.
The third limitation is that the cross-sectional naturalistic study design is ill suited to making causal interpretations about the associations documented herein between conditions and disability. Unmeasured common causes might influence these associations. In the case of the net coefficients, a related problem is that the incremental effect of each condition was evaluated after controlling for all other conditions even though some of these other conditions might have been consequences of the focal condition. This means that indirect effects of a focal condition on disability mediated by a comorbid condition (eg, an effect of cancer on disability due to cancer causing depression and depression causing disability) are excluded from the simulation. This will generally lead to an underestimation of the true effect of conditions on disability.
The fourth limitation is that we examined aggregate patterns in the total population rather than only among the employed. This means that we estimated the effects of conditions on days out of role rather than on days out of work. The relative effects of different conditions on days out of work among employed people might differ from the results reported herein, both because of differences in relative prevalence (ie, because some conditions are more important than others in influencing whether a person is employed) and because of differential effects on missing days of work and on missing days of other role activities (eg, days out of role on weekends among employed people and days out of role among homemakers or retired people).