Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

413m.doc

584 views

Published on

  • Be the first to comment

  • Be the first to like this

413m.doc

  1. 1. The impact of major depressive disorder on general functioninghealth- related quality of life, work productivity and health care utilization in relation to physical co-morbidities among individuals from the general population Baune BT 1,2, Adrian I 2, Jacobi F 3 1 Department of Psychiatry, School of Medicine, James Cook University, Australia 2 Department of Psychiatry, University of Muenster, Germany 3 Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Germany Running head “Co-morbid MDD and physical diseases” Address for Correspondence Assoc Prof Bernhard T. Baune Department of Psychiatry School of Medicine James Cook University Queensland 4811 AUSTRALIA Phone: +61 7 4781 6731 1
  2. 2. Fax: +61 7 4781 5945 Email: bernhard.baune@jcu.edu.au Abstract Objective: To analyze the impact of major depressive disorder (MDD) on general functioninghealth related quality of life, work productivity and health care utilization in relation to a variety and number of co-existing physical diseases in the general population. Methods: 4,181 participants from a community sample were interviewed and 12-months- MDD (CIDI) and 12-months medical diagnoses were made after medical examination. General functioning was evaluated with MOS-SF36. Doctor visits in primary care Outpatient doctor visits and work productivity were assessed by self report for the past 12 months. Results: While general functioning demonstrated substantial impairment across a variety of physical diseases and MDD, no pattern was found for certain entities of physical diseases. The number of co-existing physical diseases had a major impact on the decline of general functioning among participants with co-existing MDD.Results: While we found a general decline of the mental summary score due to MDD across all entities of physical diseases, we could not show the same broad effect of MDD on the physical summary scores of each physical disease entity. Only MDD subjects with allergic and neurological disorders had a worse physical quality of life compared to their counterparts. Another main finding of this study is that the number of co-existing physical diseases has a significant impact on the decline of the physical and mental domain of quality of life depending on the MDD status. Co-morbid MDD significantly increased the number of doctor visits across various physical diseases as well as days of lost work for the past 12 months. Conclusions Our findings point to the need for comprehensive clinical assessments of people with co- morbid physical diseases and MDD as the impact of QOL is high. 2
  3. 3. Key words: major depressive disorder –comorbidity – primary health care – quality of life 3
  4. 4. Introduction Unipolar depression is currently the leading cause of disability in developed countries (1), and the fourth leading cause of disability worldwide (2). Projections estimate that major depressive disorder (MDD) will rise to be the second leading cause of disability worldwide by the year 2020 (3, 4). Major depression and depressive symptoms impair health-related quality of life. and general functioning and cause a huge economic burden (direct and indirect health care costs) (5, 6). Direct costs include mental health treatment costs of depression and all other health care costs. Indirect costs include such varied factors as lost wages for the depressed individual and caregiver burden (7). Health-related quality of life declines most among patients who, in addition to depression, suffer from a long-term somatic disease. The impact of untreated major depression on functioning ability is at least equal to that of many somatic conditions, including low-back pain, arthritis, diabetes and cardiac disease. In a 2-year follow-up study comparing the disability induced by depression, diabetes, hypertension, a recent myocardial infarction and/or congestive cardiac disease, the functional limitations caused by depression were the same as those caused by somatic disease throughout the follow-up period (8). Patients with chronic physical illness are known to have a high prevalence of co-morbid depression (6)9). The cross-sectional prevalence of major depression in general hospital patients has been consistently found in many studies to be about 15% (7)10). In medically ill patients co-morbidity from a depressive disorder is due to major depression in 30-50% and 50-70% due to minor depression/dysthymia (8)11). The severity of depression may differ among different medical disciplines (e.g. there is severe depression in general surgical patients and less severe depression in gynaecology and rehabilitation patients) (8, 9)(11, 12). Furthermore, both major depressive disorder and subsyndromal depression have been associated with increased somatic symptoms, morbidity, mortality, health care utilization, and costs in the presence of co-morbidities (6, 10-12)(9, 13-15). The importance of health-related quality of life in the assessment process of mental conditions has been demonstrated by Rapaport et al. They found that diagnostic-specific symptom measures explained only a small proportion of the variance in health-related quality of life, suggesting that an individual’s perception of quality of life is an additional factor that should be part of a complete medical assessment (1316). Most of the studies assessing health-related quality of life, general functioning and health care utilization in depressed individuals with co-morbid medical conditions have been carried out in general hospitals and primary care settings. These studies investigated either patients of a 4
  5. 5. certain age group exhibiting a higher prevalence of medical conditions (e.g. elderly patients) or patients with specific medical conditions (e.g. heart failure, renal diseases). Thus, the current available knowledge on the association of depression, medical co-morbidity and, health-related quality of life and impact on relies mostly on clinical studies with a selection bias of certain medical conditions, medical disciplines and age groups. These clinical studies may lack representiveness and generalizability of the findings. Moreover, they have largely investigated the relationship between the severity and chronicity either of depression or physical illnesses and quality of life, and have failed to shownot examined the impact of a range of entities of physical diseases and the number of physical diseases with co-existing major depression on health-related quality of life, general functioning and health care utilization. Aims of the study The aimaims of this study in the general population waswere to analyze the dimensions of health-related quality of life, general functioning and health care utilization in relation to the varietyentity and number of physical diseases among individuals with and without and with coexisting major depressive disorder (MDD). Our hypotheses were: 1. Both depression and physical diseases decrease dimensions of health-related quality of life. We expected that the association of depression and physical diseases with health-related quality of life would show a disease specific reduction of dimensions of health-related quality of lifeIn the first hypotheses we investigated the impact of the entity of physical diseases on the physical and mental summary score of the SF36 among subjects with MDD compared to those without MDD. First we expected a similar decline of physical and mental quality of life across different physical diseases. Second, we expected that the presence of a MDD would further decline the physical and mental health related quality of life across all physical diseases. 2. Health-related quality of life diminishes with increasing numbers of medical conditions in both patients with and without MDD.We examined the impact of the number of physical diseases on the physical and mental summary score of the SF36 among subjects with MDD compared to those without MDD. It was expected that the physical and mental quality of life diminishes with the number of physical diseases regardless of the presence of a MDD. 3. In our third hypotheses we assume that the presence of a 12-month major depressive disorder increases the number of both direct and indirect health costs (primary health careand 5
  6. 6. specialist visits and disability days) among participants with co-morbid physical diseases. We expected to find an increase in doctor visits and disability days across all physical diseases when a MDD was present. Materials and methods Sample For this analysis we used the data set of the German National Health Interview and Examination Survey (GHS) that provided diagnoses for affective disorders (14, 15)(17, 18). The study consisted of a core survey (GHS-CS) and a mental health supplement (GHS-MHS). The sample of the core survey was drawn from the population registries of subjects aged 18 to 79 years living in Germany in 1997 yielding a representative sample of eligible 13,222 persons according to age, sex, and community-type criteria. The response rate of the core survey was 61.4% (n=7,124) (16-18)(19-21). Data collection was done between October 1997 and March 1999. After the completion of the core survey, a representative sample for the mental health assessment was drawn from the study population of the core survey (N=7,124). A screening questionnaire (CID-S) for mental disorders was administered at the end of the medical examination of the core health survey. A structured, clinical interview (Composite International Diagnostic Interview - M-CIDI) was subsequently used to obtain DSM-IV disorder diagnosis in all participants from the core survey who screened positive and 50% of those who screened negative for a mental disorder (15)18). Non-response did not differ significantly between screen-negative and screen-positive respondents from the main survey (19)22). Data were weighted by demographic characteristics and by selection probabilities in the later analyses. Most interviews were done within 2 to 4 weeks after the core survey medical examination. Assessment of physical conditions The core survey consisted of (1) a self-report questionnaire, (2) a standardized computer- assisted medical interview, (3) anthropometric and blood pressure measurements and the collection of blood and urine samples, and (4) a screening for mental disorders, which served as the first stage of the Mental Health Supplement (GHS-MHS). All examinations and interviews were done in study centres at the respective site. The self-report questionnaire evaluated the subjects’ current and past somatic symptoms and complaints, health care utilization, and impairments and disabilities. Completion of this questionnaire was followed 6
  7. 7. by a face to face computer assisted interview by a study physician. Diagnoses of any somatic disorder were made by the physician after physical examination and diagnoses were revised on the basis of medical reports and of the laboratory test results that became available two weeks later (20, 21)(23, 24). For this analysis we used 12-months prevalence of physical illnesses as well as MDD. Physical diseases were grouped into larger disease entities. Allergies (1) consisted of eczema, neurodermatitis, contact allergy, food allergy, nettle rash, hay fever. Endocrine and metabolic diseases (2) consisted of thyroid disease, diabetes, and hyperlipidaemia. Cardiovascular disorders (3) included the single diseases hypertension, coronary heart disease, and stroke. Gastrointestinal diseases (4) were made up of gastritis, ulcer and liver diseases, neurological disorders (5) consisted of Parkinson’s disease, multiple sclerosis, epilepsy, encephalitis, and migraine and respiratory diseases (6) consisted of asthma and chronic obstructive pulmonary disease (COPD). Assessment of Mental Disorders Due to the psychometric properties of the Composite International diagnostic Interview (CIDI) the Mental Health Survey included only persons from the age of 18 to 65 years (22)25). Details of the psychometric properties of the CIDI are reported elsewhere (23)26). The resulting response rate of the age restricted sample was 87.6%, yielding a total of 4,181 respondents, aged 18-65 years who completed both the core survey for physical assessment and the GHS-MHS for mental assessment. In this analysis major depressive disorder (MDD) was considered as the diagnostic entity of interest. MDD is characterized by a persistently sad or irritable mood, difficulties in thinking, concentrating, and remembering, physical slowing or agitation, anhedonia, thoughts of guilt, worthlessness, hopelessness, and emptiness and persistent physical symptoms that do not respond to treatment. MDD includes single and recurrent depressive episodes. MDD in the course of bipolar disorders was not included in the analyses. Assessment of Quality of Life The MOS-SF-36 was developed as part of the Medical Outcome Study in the 1980s (24, 25) (27, 28). In non-psychiatric populations the SF-36 has shown a good validity and reliability and is one of the most frequently used instruments world-wide for measuring health care outcomes. It has been validated within psychiatric populations, e.g. in depressive subjects (26)29) and in outpatient schizophrenic subjects. In addition to the two overall scores of 7
  8. 8. physical and mental health related QOL, the SF-36 questionnaire includes the following health dimensions: general health, mental health, vitality, pain, physical role functioning, emotional role functioning, and social functioning. The instrument is translated into many languages (27)30) including German (2831). Assessment of associated cost factorshealth care utilisation and work productivity Health care utilization in terms of the sum of all self reported outpatient doctor visits in the last 12 months (general practitioner and a range of specialists) was used to determine the role of co-morbid depression for direct medical cost factors. Participants specified the exact number of doctor visits in the last 12 months selecting from a given list of 18 medical specialties. Self reported work loss days of the preceding 12 months were used to indicate for indirect costs of illness. Here, analyses were limited to the respondents working at least part- time. Statistical analysis 12-months period prevalence rates of depression and physical diseases were estimated. Comparisons of sociodemographic variables between groups were made with the Chi-square test for categorical variables. Comparisons of quality of life (SF-36) between groups were carried out with one-way ANOVA procedure. Since the count variables “number of work loss days” and “number of doctor visits” were extremely skewed we analysed these with Mean Ratios based on negative binomial regression (MR; one-sided tests, adjusted for sex and age). The MR can be interpreted as increase in %; significant results are reported with 95%- confidence intervals. Data were weighted by the standard procedure applied to the GHS-MHS according to demographic characteristics (age, gender, and geographical location) and selection probabilities (18)21). Analyses were conducted using the Statistical Package for Social Science SPSS V12.0 (2932). Results Study populationSample and disease prevalence In total, 4,181 participants aged 18-65 years were assessed for mental health disorders. About 49.7% of the sample were women, mean age of all participants was 43.5 years (SD 11.6). The 12-month prevalence of MDD was 8.3% (N=347), it was 24.4% (N=1,018) for endocrine and metabolic diseases (thyroid disease, diabetes, hyperlipidaemia), 24.0% (N=1,001) for 8
  9. 9. allergies (eczema, neurodermatitis, contact allergy, food allergy, nettle rash, hay fever), 14.5% (N=606) for cardiovascular disorders (hypertension, coronary heart disease, stroke), 10.8% (N=453) for neurological disorders (Parkinsonism, Multiple Sclerosis, epilepsy, encephalitis, migraine), 9.6% (N=400) for gastrointestinal diseases (gastritis, ulcer, liver diseases), and 7.6% (N=318) for respiratory diseases (asthma, COPD). All physical diseases were significantly more frequent in women than in men (Chi2-test: p<0.001), except for cardiovascular diseases (females and males both 14.5%) and pulmonary diseases (female : male = 8.0% : 7.3%). Taking all single physical diseases into account, on average 1.8 diseases were observed per study participant (SD 1.8; min.: 0; max.: 10). Females reported a statistically significant higher mean number of physical diseases compared to males (2.1: 1.5; p<0.001). Gender, age, social class and diseases A 12-month MDD was significantly more frequent among women compared to men (sex ratio: 2.02:1; p<0.001). MDD showed a non-significant peak among the 40-49 years old (9.8%) and no significant association was found with social status in this sample. While the frequency of allergies significantly declined with age, all other physical diseases showed statistically significant increased proportions at higher age groups (Chi2-test: p<0.001). Pulmonary diseases were an exception as they showed non-significant peaks (24.5%) for the age groups 30-39y and 50-59y. When we compared low vs. high social class for physical diseases, we found that allergy was significantly more frequent in the higher social class (Chi2-test: p<0.01) and all other physical diseases were significantly more frequent in the lower social class (Chi2-test: p<0.05), except neurological disorders that showed similar 12- month prevalence rates in both social classes (10.3% vs. 10.1%). Table 1 shows the 12-month prevalence of MDD and physical diseases stratified by gender. MDD and all physical diseases were significantly more frequent in women than in men (Chi2- test: p<0.001), except the cardiovascular diseases (females and males both 14.5%) and respiratory diseases (female : male = 8.0% : 7.3%). [Insert Table 1 about here] Quality of life, physical diseases and MDD Results on the two overall SF-36 sum scores of physical and mental health-related quality of life showed a consistent decline across all in relation to various entities of physical diseases 9
  10. 10. andare presented in table 2. MDD. Major depressive disorder showed a significant decline on the overall physical (mean 47.3, SD 9.4; p<0.001) and mental (mean 40.9, SD 11.3; p<0.001) SF-36 sum scores. While participants with allergies (physical sum score: mean 48.7, SD 8.7, p<0.05; mental sum score: mean 49.1, SD 9.4, p<0.001), neurological disorders (physical sum score: mean 45.8, SD 9.4, p<0.001; mental sum score: mean 47.8, SD 10.8, p<0.001), respiratory diseases (physical sum score: mean 45.6, SD 9.6, p<0.001; mental sum score: mean 48.8, SD 9.9, p<0.001) and gastrointestinal disorders (physical sum score: mean 45.5, SD 10.2, p<0.001; mental sum score: mean 48.1, SD 10.4, p<0.001) scored significantly lower both on the physical and mental SF-36 sum scores than individuals without these physical diseases, subjects with endocrine-metabolic (physical sum score: mean 45.9, SD 9.9, p<0.001; mental sum score: mean 50.1, SD 10.1, p>0.05) or cardiovascular diseases (physical sum score: mean 44.2, SD 10.4, p<0.001; mental sum score: mean 51.1, SD 9.5, p>0.05) scored significantly lower on the physical but not on the mental SF-36 sum score compared to those without these disorders. was most prevalent in subjects with allergies, neurological or gastrointestinal disorders. The physical summary score was significantly lower in subjects with MDD having co-morbid allergies or neurological disorders compared to their counterparts without MDD. Figure 1 illustrates mean scores of dimensions of health-related quality of life depending on the number of physical diseases (single count of all included physical diseases) among subjects without MDD, as well as for individuals with pure MDD (i.e. not co-morbid with the included physical diseases). The figure shows a reverse linear relationship between the number of physical diseases and the scores on dimension 1-4: an increasing number of physical diseases yields in a gradual decrease of scores on the dimensions 1-4, which mainly represent the physical dimensions of health-related quality of life. A different picture results for the dimensions 5-8, which cover general health perception and psychosocial dimensions of quality of life. Although a remarkable reduction of scores on dimensions 5-8 according to the number of physical diseases is found here, the amount of the reduction is less prominent than for the first 4 dimensions of quality of life. Another interesting observation in Figure 1 is related to the comparison of scores between individuals with pure MDD (without physical disease) and the subject groups according to the number of physical diseases. While MDD is associated with a moderate decline on scores of the physical dimensions 1-4 of quality of life similar to individuals with 1 or 2 physical diseases, MDD is related to a substantial decline of health related quality of life on the 10
  11. 11. dimensions 5-8 comparable to individuals with 5 co-morbid physical diseases (and without MDD). [Insert Figure 1 about here] Table 1 shows mean scores of single dimensions of health-related quality of life depending on the number of co-existing physical diseases for participants with and without co-morbid 12-month MDD. We found a general statistically significant decline of health-related quality of life dimensions by an increasing number of physical diseases which was true for participants with and without a co-morbid MDD (F-value of ANOVA). The only exception applied to the SF36 dimension ‘vitality’ for participants with MDD: the decline of scores on this dimension across the number of physical diseases did not reach statistical significance. Further results of table 1 show that the co-existence of MDD with any of the physical diseases led to a further decline of health-related quality of life (compared to those without MDD). This finding became statistically most evident for the dimensions bodily pain, general health perception, social functioning, role limitations due to emotional problems and mental health. Although MDD led to a decrease also on the dimensions physical functioning and role limitations due to physical problems, the differences between the groups were of inconsistent statistical significance. In contrast, we found significantly decreased mental summary scores for subjects with MDD across all entities of physical disorders compared to their counterparts without MDD. [Insert Table 2 about here] Table 3 presents data on the impact of the number of physical diseases on the physical and mental summary scores of the SF36 among subjects either with or without MDD. While an increasing number of physical diseases were related to a significant decline of the physical summary score among both subjects with and without MDD, we found a significant decline on the mental summary score only for individuals without MDD. When the physical and mental quality of life scores were compared for subjects with MDD to those without MDD according the grouped number of co-morbid physical diseases (0, 1, 2,… physical diseases), we was observed that participants with MDD and no or 1 co-morbid physical disease scored significantly lower on the physical summary score compared to their counterparts. Interestingly, subjects with MDD scored significantly lower on the mental summary score regardless of the number of co-morbid physical disorders compared to their counterparts without MDD (table 3). 11
  12. 12. [Insert Table 3 about here] Health care utilization and loss of work productivity Figure 21 indicates differences in health care utilization in terms of self reported outpatient doctor visits (last 12 months) for people with and without a 12-months diagnosis of MDD. For the whole group, outpatient doctor visits were elevated by 45% if MDD was present (MR=1.45, 95%cCI=1.31-1.60; p<0.01). With the exception of respiratory diseases (insignificant trend, p<0.15), all somatic diseases were significantly associated with higher numbers of doctor visits when a MDD co-existed (MR=1.24-1.47; p<0.01-0.05). Figure 32 indicates differences in work loss days (last 12 months) for people from the workforce (working at least part-time; N=2,714) with and without a 12-months diagnosis of MDD. For the whole group, work loss days were elevated by 40% if MDD was present (MR=1.40, 95%ci=1.13-1.74; p<0.01). A trend of an increase of lost days of work productivity when MDD co-existed was found in respiratory, allergic, cardiovascular and gastrointestinal diseases without reaching significance (p-value between p<0.15 to p<0.22). Significant differences were found for endocrine/metabolic (MR=1.63, 95%CI=1.00-2.65; p<0.05) and neurological diseases (MR=2.47, 95%CI=1.52-4.00; p<0.01) with co-morbid MDD. Depressed people were less likely to be in the workforce than people without MDD (54% vs. 67%; p<0.00). We repeated these analysis for the whole sample as well (i.e. including respondents that were unemployed, retired, homemaker, students etc. not belonging to the workforce), and found distributions of self reported disability days (not being able to carry out usual activities) were basically the same. [Insert Figures 2 1 and 3 2 about here] Discussion In this population-based study we investigated the association of MDD and various physical diseases with general functioning and, health-related quality of life and health care utilization. As opposed to clinical studies with a possible help-seeking bias the sample can be regarded as representative for the adult population aged 18-65. Consistent with previous studies that employed a variety of instruments to measure health-related quality of life (30-34)(33-37), our examination of health-related quality of life and general functioning demonstrated substantial impairment in health-related quality of life across subjects with physical diseases 12
  13. 13. and MDD. In addition to these findings, our results showed a similar decrease of health- related In this study we found that MDD was associated with reduced physical and mental quality of life across a wider spectrum of physical diseases (except individuals with allergic disorders) which is a new finding from a single study. This finding indicates that the individuals under study experienced a similar impairment of their physical diseases despite the entity of the disease. In this study we found that MDD was associated with reduced quality of life to a larger extent than various physical conditions which is confirmed by many studies, that reported a worse subjective health perception in depressed individuals (35, 36)(38, 39). The authors of the Medical Outcomes Study already concluded that the functioning of depressed patients is comparable to or even worse than that of patients with major chronic physical conditions (24, 26)(27, 29). The results of our study, however, indicate new aspects of the relationship between MDD, physical diseases and health-related quality of life. While we could not show a physical disease specific reduction of dimensions of health-related quality of life, we found that MDD implies a specific pattern of reduction of certain dimensions of quality of life. Whereas MDD together with single or multiple co-existing physical diseases has little influence on the physical dimensions of health-related quality of life, a statistically significant diminishing effect on the different psychosocial dimensions of quality of life was observed for co-existing MDD and physical diseases compared to individuals with pure physical diseases. While we found a general decline of the mental summary score due to MDD across all entities of physical diseases, we could not show the same broad effect of MDD on the physical summary scores of each physical disease entity. Only MDD subjects with allergic and neurological disorders had a worse physical quality of life compared to their counterparts. This finding is partly conflicting with the study by Saarijarvi et al. who reported that major depression per se seems to explain the broad decline in quality of life among depressive patients with co- existing physical diseases (33)36). These authors, however, did not take into account the numberdiagnostic entities of co-existing physical diseases, which might account for the differences between both studies. Moreover, we found that participants experiencing two or more co-existing physical diseases and no MDD may have a worse quality of life than those individuals with MDD These effects of MDD on the physical and none or only one co-existing physical disease. 13
  14. 14. The effects of MDD on physical and psychosocial dimensionsmental domains of quality of life reported in our study may help to better understand the specific problems these patients present with to their physician. An improved understanding of the patterns of a decline of quality of life across the various dimensionstwo quality of life domains is suggested to be beneficial for the diagnostic evaluation of patients with major depression (13)16). On the other sideOur results indicate that despite the presence of a MDD the physical domain of quality of life does not necessarily be worse than in subjects without MDD. In conclusion, however, MDD should not be overseen and these patients require treatment of their depression. In addition, physicians need careful consideration of a co-existing major depression among patients with single or even multiple co-morbid physical diseases indicated by lower scores on the dimensionsmental domain of health-related quality of life. Moreover, in Another main finding of this study we found is that the number of co-existing physical diseases has a major significant impact on the decline of quality of life among participants with MDD plus co-existing physical diseases as well as among participants with pure physical diseases (without MDD). This effect was also observed in a study by Small et al. among patients with geriatric depression the physical and mental domain of quality of life depending on the MDD status. While an increasing number of co-existing physical diseases in participants either with or without MDD showed a significant linear reduction of scores on the physical domain, the mental domain of health-elated quality of life was only affected by the number of physical diseases in participants without MDD, but not in those with MDD. The finding of this study about the physical domain is consistent with other studies of both young and older adults. In a 2-year observational study of 1790 adult outpatients with depression and various physical diseases, Hays et al. found that physical limitations from depression were similar to or worse than those from chronic physical illnesses (31)8). However, the comparability between their study and our research is limited as those authors did not compare depressed individuals with co-existing physical diseases to those without depression. In this sense the validity of this comparison is improved in our study. While an increasing number of co-existing physical diseases in participants without MDD showed a linear reduction of scores on the physical dimensions (physical functioning, role limitations due to physical problems), the psychosocial dimensions (social functioning, role limitations due to emotional problems) of health-elated quality of life and general health perception were relatively little affected by the number of physical diseases in participants without MDD. In contrast, MDD was significantly associated with a further decline of health- related quality of life in the presence of one or more co-morbid physical diseases showing a 14
  15. 15. prominent effect for the psychosocial dimensions of quality of life. In the present analysis, the finding that depressed participants with greater numbers of physical illness were more likely to experience worse physical well-being and functioning is consistent with other studies of both young and older adults. In a 2-year observational study of 1790 adult outpatients with depression and various physical diseases, Hays et al. found that functional limitations from depression were similar to or worse than those from chronic physical illnesses Beyond that, it appeared that the presence of MDD was the main factor impacting on the mental domain of quality of life rather than the number of physical diseases. This finding may also have diagnostic implications for physicians. One should consider the presence of a MDD even in patients with various physical diseases and low mental quality of life, because MDD mainly accounts for the low mental quality of life and not necessarily the physical diseases. Available treatment of depression might increase the mental quality of life significantly despite a larger number of co-morbid physical diseases. Overall, our study results may support the notion that the number of co-morbid physical diseases is more important to predict physical and mental quality of life than the specific disease entity. A study by Koopmans and Lamers found similar results although they used different outcome measures. In a community study they found a partial association between the type of physical condition, psychological distress, and fatigue and strong associations between the number of chronic physical conditions, on the one hand, and psychological distress and fatigue, on the other (5)40). As we also investigated the effects of MDD on health care utilization and work productivity in the presence of physical diseases, it was found that a co-morbid MDD significantly increased the number of outpatient doctor visits across all physical diseases. The number of excess lost days of work productivity during the last 12 months associated with co-morbid depression was elevated in all physical diseases but reached significance only for endocrine/metabolic and neurological conditions. Several previous studies confirm the impact of major depression on increased health care utilization and loss of work productivity due to depression (37-40)(41-44). However, none of these studies has evaluated whether depression leads to an excess of doctor visits and loss of work productivity among participants with major depression and co-existing physical diseases. Our findings suggest treatment of depression also in cases with a history of one or more physical diseases in order to reduce the number of doctor visits and days of lost work productivity. Our research is also interesting in light of previous studies showing that treatment and recovery from depression is associated with significant reductions in work disability and possible reductions in health care costs 15
  16. 16. (41)45). Further studies are needed to evaluate whether this finding is robust in the presence of physical diseases among depressed individuals. Limitations: With the available data of this cross-sectional study we could not establish a clear time sequence between the occurrence of MDD and physical diseases and its effects on quality of life, health care utilization and work productivity. It is important in future cross- sectional (providing retrospective onset data) and longitudinal studies to control for treatment effects on physical diseases and MDD at the same time when measuring outcome. Although this population-based study excluded long-term (>3 months) hospitalised patients, like terminally ill patients, it is most likely that our findings and conclusions are applicable also to the more severely ill individuals. However, our findings are not representative for long-term hospitalized patients. A further limitation is the restriction to subjects up to 65 years. For older individuals where multi-morbidity rapidly increases with age possibly different patterns have to be investigated in further studies; here, also age-specific particularities in the assessment of depression have to be considered (22). As we used self-reported data on doctor visits and work productivity, we need to take into account information and recall bias potentially influencing the results. Future studies should use whenever possible objective data such as claim data or extracted data from databases kept by health car providers. In summary, MDD impacts on reduced physical quality of life in co-morbid allergic and or neurological disorders and MDD significantly decreases the mental quality of life across all investigated entities of physical diseases. The number of co-morbid physical diseases has a major impact on the physical domain quality of life among participants with or without MDD and on the mental domain of quality of life only in participants without MDD. We can conclude that general condition seem to influence health-related quality of life rather than certain disease entities. General practitioners and other doctors in primary health care may find this observation important for diagnostic and treatment procedures as the specific patterns of impaired health-related quality of life reveal additional diagnostic information whether a single physical disease, a single MDD with somatic symptoms or a co-morbid condition is present. To apply these findings in clinical practice doctors would need more time for assessment. Another main conclusion from this study for future research is to consider the number and type of co-morbid physical diseases when rating health-related quality of life among both subjects groups with and without MDD. Acknowledgements 16
  17. 17. The German National Health Survey (GHS) was supported by grant 01EH970/8 (German Federal Ministry of Research, Education and Science; BMBF). We thank Hans-Ulrich Wittchen, PhD, Heribert Stolzenberg, PhD, and Bärbel-Maria Kurth, PhD, for their assistance with the BGS Public use databases. References 1. Wells KB, Strom R, Sherbourne CD, Meredith LS: Caring for depression: A RAND study. Cambridge, Harvard University Press, 1996 2. Murray CJL, Lopez AD: Alternative projections of mortality and disability by cause, 1990-2020: global burden of disease study. Lancet 349:1498-504, 1997 3. Murray CJL, Lopez AD: Global mortality, disability, and the contribution of risk factors: global burden of disease study. Lancet 349:1436-42, 1997 17
  18. 18. 4. Paykel ES, Brugha T, Fryers T: Size and burden of depressive disorders in Europe. Eur Neuropsychopharmacol 15:411-23, 2005 5. Hays RD, Wells KB, Sherbourne CD, Rogers W, Spritzer K: Functioning and well- being outcomes of patients with depression compared with chronic somatic illnesses. Arch Gen Psychiatry 52:11-9, 1995 5. Berto P, D'Ilario D, Ruffo P, Di Virgilio R, Rizzo F: Depression: cost-of-illness studies in the international literature, a review. J Ment Health Policy Econ 3:3-10, 2000 6. Hu TW: The economic burden of depression and reimbursement policy in the Asia Pacific region. Australas Psychiatry 12 Suppl:S11-5, 2004 7. Booth BM, Zhang M, Rost KM, Clardy JA, Smith LG, Smith GR: Measuring outcomes and costs for major depression. Psychopharmacol Bull 33:653-8, 1997 8. Hays RD, Wells KB, Sherbourne CD, Rogers W, Spritzer K: Functioning and well- being outcomes of patients with depression compared with chronic somatic illnesses. Arch Gen Psychiatry 52:11-9, 1995 9. Katon WJ: Clinical and health services relationships between major depression, depressive symptoms, and general medical illness. Biol Psychiatry 54:216-26, 2003 10. Arolt V: Die Häufigkeit psychischer Störungen bei körperlich Kranken. In Diefenbacher A (ed), Psychiatrie in der klinischen Medizin. Darmstadt, Steinkopf, 2003 11. Arolt V, Rothermundt M: Depressive disorders in patients with somatic illnesses. Nervenarzt 74:1033-1054, 2003 12. Wancata J, Windhaber J, Bach M, Meise U: Recognition of psychiatric disorders in nonpsychiatric hospital wards. J Psychosom Res 48:149-155, 2000 1013. Mancuso CA, Peterson MG, Charlson ME: Effects of depressive symptoms on health- related quality of life of asthma patiens.patients. Gen Intern Med 15:301-301, 2000 18
  19. 19. 1114. Felker B, Katon W, Hedrik SC, et al. e: The association between depressive symptoms and health status in patients with chronic pulmonary disease. Gen Hosp Psychiatry 23:56-61, 2001 1215. Hunkeler EM, Spector WD, Fireman B, Rice DP, Weisner C: Psychiatric symptoms, impaired function, and medical care cost in an HMO setting. Gen Hosp Psychiatry 25:178-184, 2003 1316. Rapaport MH, Clary C, Fayyad R, Endicott J: Quality-of-life impairment in depressive and anxiety disorders. Am J Psychiatry 162:1171-1178, 2005 1417. APA: Diagnostic and Statistical Manual of Mental Disorders [4th ed] (DSM-IV), 1994 1518. World-Health-Organization: Composite International Diagnostic Interview [CIDI Version 2.1]. 1997 1619. Bellach B: Der Bundesgesundheitssurvey. Gesundheitswesen 60:S59-S114, 1998 1720. Wittchen H-U, Mueller N, Storz S: [Psychiatric disorders: incidence, psychosocial effects and correlation with physical illnesses] Psychische Störungen: Häufigkeit, psychosoziale Beeinträchtigungen und Zusammenhänge mit körperlichen Erkrankungen. Gesundheitswesen 60:S95-S100, 1998 1821. Jacobi F, Wittchen HU, Holting C, Sommer S, Lieb R, Hofler M, Pfister H: Estimating the prevalence of mental and somatic disorders in the community: aims and methods of the German National Health Interview and Examination Survey. Int J Methods Psychiatr Res 11:1-18, 2002 1922. Carter RM, Wittchen HU, Pfister H, Kessler RC: One-year prevalence of subthreshold and threshold DSM-IV generalized anxiety disorder in a nationally representative sample. Depress. Anxiety 13:78-88, 2001 2023. Wiesner G, Grimm J, Bittner E: Notes on the Myocardial Infarction Scene in the Federal Republic of Germany: Prevalence, Incidence, Trends, Comparison between Eastern and Western Germany. Gesundheitswesen 61:S72-S78, 1999 19
  20. 20. 2124. Wiesner G, Grimm J, Bittner E: Stroke: incidence, prevalence, trends, comparison between Eastern and Western Germany. Gesundheitswesen 61:S79-S84, 1999 2225. Knauper B, Wittchen HU: Diagnosing major depression in the elderly-Evidence for response bias in standardized diagnostic interviews. J. Psychiatr. Res. 28:147-164, 1994 2326. Wittchen HU: Reliability and validity studies of the WHO-Composite International Diagnostic Interview (CIDI): a critical review. J. Psychiatr. Res. 28:57-84, 1994 2427. Tarlov AR, Ware JE, Greenfield S, Nelson EC, Perrin E, Zubkoff M: The Medical Outcome Study. An application of methods for monitoring the results of medical care. Jama 262:925-930, 1989 2528. Ware JE, Sherbourne CD: The MOS 36-Item Short-Form Health survey (SF-36). I. Conceptual framework and item selection. Med Care 30:473-483, 1992 2629. Wells KB, Stewart A, Hays RD, Burnam MA, Rogers W, Daniels M, Berry S, Greenfield S, Ware J: The functioning and well-being of depressed patients. Results from the Medical Outcome Study. Jama 262:914-919, 1989 2730. Gandek B, Ware JE JrJEftIPG: Methods for validating and norming translations of Health Status QuestionnaireQuestionaire: The IQOLA Project Approach. J Clin Epidemiol 51:953-959, 1998 2831. Bullinger M: German translation and psychometric testing of the SF-36 Health Survey: Preliminary results from the IQOLA Project. Soc Sci Med 41:1359-1366, 1995 2932. SPSS-for-Windows: SPSS Inc. Headquarters, 233 S. Wacker Drive 11th-floor. Chicago, Illinois 60606, Release 12.0 3033. Noel PH, Williams JW, Jr., Unutzer J, Worchel J, Lee S, Cornell J, Katon W, Harpole LH, Hunkeler E: Depression and comorbid illness in elderly primary care patients: 20
  21. 21. impact on multiple domains of health status and well-being. Ann Fam Med 2:555-62, 2004 3134. Small GW, Birkett M, Meyers BS, Koran LM, Bystritsky A, Nemeroff CB: Impact of physical illness on quality of life and antidepressant response in geriatric major depression. Fluoxetine Collaborative Study Group. J Am Geriatr Soc 44:1220-5, 1996 3235. Michalak EE, Tam EM, Manjunath CV, Solomons K, Levitt AJ, Levitan R, Enns M, Morehouse R, Yatham LN, Lam RW: Generic and health-related quality of life in patients with seasonal and non-seasonal depression. Psychiatry Res 128:245-51, 2004 3336. Saarijarvi S, Salminen JK, Toikka T, Raitasalo R: Health-related quality of life among patients with major depression. Nord J Psychiatry 56:261-4, 2002 3437. Papakostas GI, Petersen T, Mahal Y, Mischoulon D, Nierenberg AA, Fava M: Quality of life assessments in major depressive disorder: a review of the literature. Gen Hosp Psychiatry 26:13-7, 2004 3538. Spitzer RL, Kroenke K, Linzer M, Hahn SR, Williams JB, deGruy FV, 3rd, Brody D, Davies M: Health-related quality of life in primary care patients with mental disorders. Results from the PRIME-MD 1000 Study. Jama 274:1511-7, 1995 3639. Wells KB, Sherbourne CD: Functioning and utility for current health of patients with depression or chronic medical conditions in managed, primary care practices. Arch Gen Psychiatry 56:897-904, 1999 3740. Koopmans G, Lamers L: Chronic conditions, psychological distress and the use of psychoactive medications. J Psychosom Res:115-23, 2000 41. Crown WH, Finkelstein S, Berndt ER, Ling D, Poret AW, Rush AJ, Russell JM: The impact of treatment-resistant depression on health care utilization and costs. J Clin Psychiatry 63:963-71, 2002 3842. Lecrubier Y: The burden of depression and anxiety in general medicine. J Clin Psychiatry 62 Suppl 8:4-9; discussion 10-1, 2001 21
  22. 22. 3943. Wang PS, Beck AL, Berglund P, McKenas DK, Pronk NP, Simon GE, Kessler RC: Effects of major depression on moment-in-time work performance. Am J Psychiatry 161:1885-91, 2004 4044. Stewart WF, Ricci JA, Chee E, Hahn SR, Morganstein D: Cost of lost productive work time among US workers with depression. Jama 289:3135-44, 2003 4145. Simon GE, Revicki D, Heiligenstein J, Grothaus L, VonKorff M, Katon WJ, Hylan TR: Recovery from depression, work productivity, and health care costs among primary care patients. Gen Hosp Psychiatry 22:153-62, 2000 22
  23. 23. Table 1: Means (SD) of physical functioning and general well-being scores (from SF-36 scale a) in the general population according to number of physical illnesses in participants with MDD compared to those without MDD (12-months diagnoses)Tables 1-3 and Figures 1-2 Table 1: 12-months prevalence rates of major depressive disorder (MDD) and single physical diseases by gender 12-months Subject group prevalence according to number of of physical disorders illnessesGender Dimensions MDD 0 1 2 3 4 ≥5 F***, of SF36 p Physical No 93.8 92.0 (14.2) 88.1 83.8 80.9 73.2 87.9; functioning Yes (13.2) 84.3 (18.2)** (17.5) (19.8) (22.5) (24.6) <0.0001 No 92.6 89.1 (25.6) 84.8 77.9 82.5 67.3 9.3: Role Yes (11.4) 70.6 (35.9)** (19.8) (21.1)* (19.2) (23.0) <0.0001 limitations No 91.9 73.5 (23.8) 85.5 81.1 80.5 64.2 46.5; due to Yes (22.7) 59.0 (24.7)** (28.9) (33.4) (32.6) (40.7) <0.0001 physical No 85.6 70.9 (16.0) 78.7 66.2 61.9 55.0 3.2; problems Yes (31.4) 59.5 (17.1)** (33.9) (41.3)* (44.3)* (41.3) <0.01 No 76.2 62.9 (16.6) 67.8 * * 50.6 65.5; Bodily pain Yes (23.5) 47.3 (16.1)** (24.4) 63.9 61.7 (25.0) <0.0001 No 68.9 90.2 (16.3) 55.7 (23.6) (25.6) 42.0 8.1; Yes (24.7)* 71.7 (23.0)** (28.7)* 51.0 52.0 (16.7)* <0.0001 General * (22.8)* (23.6)* No 73.4 93.6 (19.8) 53.2 78.6; 23
  24. 24. health Yes (15.0) 64.9 (37.0)** 68.2 * 61.9 (21.0) <0.0001 perception No 64.9 75.2 (14.9) (17.2) 65.3 (17.0) 45.3 4.1; Yes (18.5)* 55.3 (17.5)** 61.5 (17.3) 53.7 (14.2)* <0.001 Vitality * (17.9)* 56.1 (20.3)* 52.1 28.5; 64.4 * (18.7)* * (19.8) <0.0001 (15.3) 60.2 * 57.7 Social 36.6 1.5; 53.5 (17.6) 59.8 (16.8) functioning (16.1)* >0.05 (17.8)* 46.7 (17.3) 41.9 * 23.6; * (19.4)* 45.4 (17.0)* 79.1 Role <0.0001 90.8 * (17.4)* * (23.8) limitations 3.2; (15.5) 88.2 * 86.0 due to 61.3 <0.001 78.2 (17.5) 85.8 (19.6) emotional (23.6)* 20.9; (24.0)* 68.5 (19.5) 66.4 * problems <0.0001 * (26.7)* 63.1 (27.5)* 80.7 94.7 2.3; * (24.4)* * 89.0 (35.0) Mental (18.0) 91.6 * <0.05 (27.5) 57.0 health 84.6 (22.3) 87.0 19.4; 66.2 (44.8)* (31.2)* 68.8 (28.4) <0.0001 (41.7)* * * (38.8)* 58.2 67.2 2.4; * 76.5 * (42.0)* 71.7 (18.4) <0.05 (13.4) 73.0 * (16.2) 49.5 61.7 (15.4) 73.1 53.3 (16.6)* (18.2)* 56.2 (16.3) * (19.2)* * (20.5)* 53.5 * * (16.7)* 24
  25. 25. * a SF36=36-item short-form health survey; MDD denotes major depressive disorder; Level of significance for difference between mean scores for participants with (“yes”) vs. without (“no”) MDE at *p<0.05 or **p<0.01; ***F-value and p-value of ANOVA for participants with or without MDD 25
  26. 26. Figures 1 - 3 Figure 1: Mean scores of dimensions of health-related quality of life by number of physical diseases without MDD compared to individuals with pure MDD No of physical diseases 0 1 2 3 4 ≥5 MD 100 Mean SF-36 scores (0-100) 80 60 40 20 0 1 2 3 4 5 6 7 8 Dimensions of QoL 1=physical functioning; 2=role limitations from physical problems; 3=bodily pain; 4=vitality; 5=general health perception; 6=social functioning; 7=role limitations from emotional problems; 8=mental health; MD=major depression N=4181 Total Female Male p-value * MDD (N=347) 8.3 11.2 5.5 <0.001 Endocrine / metabolic (N=1018) 24.4 28.3 20.5 <0.001 Allergic (N=1001) 23.9 28.4 19.5 <0.001 Cardiovascular (N=606) 14.5 14.5 14.5 >0.05 Neurological (N=454) 10.9 15.7 6.0 <0.001 Gastrointestinal (N=400) 9.6 11.3 7.8 <0.001 Respiratory (N=319) 7.6 8.0 7.3 >0.05 2 * p-value of Chi -test for differences of proportions between female and male subjects 26
  27. 27. 27
  28. 28. Figure 2: Self reported doctor visits within last 12 months without (N=3,834) and with (N=347) MDD within last 12 months for respiratory, allergic, endocrine/metab., cardiovascular, gastrointestinal and neurological diseases. If differences are significant (p<0.05), the Mean Ratios (MR; adjusted for sex and age) are also shown. 25 MR= MR= 1.47 1.40 MR= MR= MR= MR= 20 n.s. 1.37 1.45 1.25 1.24 doctor visits 15 no MDD MDD 10 5 0 g ab t sp l sc l ta in o r ur le st a to et re dv al ne ga dm r ca en 28
  29. 29. Table 2: 12-month prevalence rates of major depressive disorder (MDD) and quality of life sum scores by groups of medical diseases Disorders: Endocrine/ Allergic Cardiovascular Neurological Gastrointestinal Respiratory metabolic MDD in % No (N=3834) 24.0 23.2 14.6 10.1 9.0 7.4 Yes (N=347) 27.7 32.3 * 13.8 19.3 * 15.6 * 10.1 SF36 Physical summary score (Mean, SD) No MDD (N=3834) 45.9 (9.9) 48.9 (8.6) 44.3 (10.4) 49.7 (8.5) 45.5 (10.3) 45.5 (9.7) MDD (N=347) 45.2 (10.3) 46.2 (9.0) ** 43.9 (9.4) 47.6 (9.3) ** 44.6 (9.8) 45.8 (8.7) SF36 Mental Summary score (Mean, SD) No MDD (N=3834) 51.3 (9.1) 50.1 (8.6) 51.8 (8.9) 51.5 (7.8) 49.5 (9.7) 49.9 (9.2) MDD (N=347) 38.7 (11.5) ** 40.9 (11.3) ** 41.4 (10.1)** 41.3 (11.0) ** 39.7 (10.3) ** 39.3 (10.6) ** * differences of prevalence rates at p<0.01 tested with chi2-test; ** difference in means of SF36 physical or mental summary score at p<0.01 tested with student-t test; Figure 3: Table 3: Quality of life sum scores by groups of medical diseases and presence of major depressive disorder (MDD) 29
  30. 30. No of Physical Disorders: 0# 1# 2# 3# ≥4 # +F-value, p-value (N=1771) (N=1239) (N=610) (N=328) (N=233) SF36 Physical summary score (Mean, SD) No MDD (N=3834) 51.5 (7.4) 49.7 (8.1) 46.6 (9.0) 45.9 (9.4) 40.7 (11.4) 105.6; <0.001 MDD (N=347) 49.5 (8.9)* 47.5 (8.6)** 46.5 (10.5) 45.2 (8.2) 41.9 (9.6) 4.8; <0.001 SF36 Mental Summary score (Mean, SD) No MDD (N=3834) 51.8 (7.2) 51.6 (7.9) 50.7 (8.9) 50.2 (9.5) 48.7 (10.8) 8.5; <0.001 MDD (N=347) 43.2 (10.6)** 39.8 (11.5)** 39.8 (11.9)** 39.6 (10.3)** 40.6 (10.7)** 1.5; =0.183 Differences of means of the SF36 Physical and Mental summary score in participants with MDE compared to those without MDD per number (0, 1, 2, 3, ≥4) of physical disorders tested with student-t tests at a significance level of *p<0.01 and **p<0.001; + F-value and p-value for univariate analysis of variance: dependent variables are SF36 physical and mental summary scores; independent variable is the number of physical diseases; analysis of variance is done separate for subjects with MDD and without MDD; 30
  31. 31. Figure 1: Self reported doctor visits within last 12 months without (N=3,834) and with (N=347) MDD within last 12 months for respiratory, allergic, endocrine/metab., cardiovascular, gastrointestinal and neurological diseases. If differences are significant (p<0.05), the Mean Ratios (MR; adjusted for sex and age) are also shown. 25 MR= MR= 1.47 1.40 MR= MR= MR= MR= 20 n.s. 1.37 1.45 1.25 1.24 doctor visits 15 no MDD MDD 10 5 0 g ab t sp l sc l ta in o r ur le st a to et re dv al ne ga dm r ca en 31
  32. 32. Figure 2: Self reported work loss days within last 12 months among respondents in the workforce without (N=2,529) and with (N=185) MDD within last 12 months for respiratory, allergic, endocrine/metab., cardiovascular, gastrointestinal and neurological diseases. If differences are significant (p<0.05), the Mean Ratios (MR; adjusted for sex and age) are also shown. MR= 25 2.47 work loss days (in workforce) n.s. MR= 20 1.63 n.s. n.s. MR= 1.40 15 n.s. no MDD MDD 10 5 0 ab sc rg ol sp l t ta in ur le va et to re st al ne dm ga rd ca en 32

×