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Published online before print July 16, 2007, 10.1097/PSY.0b013e3180cc3062
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Psychosomatic Medicine 69:543-550 (2007)
© 2007 American Psychosomatic Society

ORIGINAL ARTICLES

Diabetes, Common Mental Disorders, and Disability: Findings From the UK National Psychiatric Morbidity Survey

Jayati Das-Munshi, MRCPsych, Rob Stewart, MD, Khalida Ismail, PhD, Paul E. Bebbington, PhD, Rachel Jenkins, MD and Martin J. Prince, MD

From the Institute of Psychiatry (J.D.-M., R.S., K.I.R.J., M.J.P.), King’s College London, London, UK, and the Department of Mental Health Sciences (P.E.B.), Royal Free and University College Medical School, London, UK.

Address correspondence and reprint requests to Jayati Das-Munshi, Section of Epidemiology, Institute of Psychiatry, King’s College London, PO 60, De Crespigny Park, London SE5 8AF, UK. E-mail: spsljdm{at}iop.kcl.ac.uk


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Objectives: To determine a) the associations between diabetes and common mental disorders in a nationally representative sample and the effect of key covariates on such associations and b) the association of comorbid common mental disorders on the quality of life and diabetes self-care indicators.

Methods: In a cross-sectional survey, people with diabetes were identified from a sample of 8580 individuals aged 16 to 74 years, drawn from the 2000 UK National Psychiatric Morbidity Survey. Diabetes was ascertained by self-report and prescribed medications. Psychiatric morbidity was assessed using the Revised Clinical Interview Schedule. Quality of life was measured using the Short Form-12, and questions were asked regarding diabetes self-care and functioning.

Results: A total of 249 individuals were identified with diabetes. People with diabetes were more likely to suffer from common mental disorders (odds ratio (OR) = 1.5; 95% Confidence Interval (CI): 1.1–2.2; p < .05), and in particular mixed anxiety and depression (OR: 1.7; 95% CI: 1.1–2.6; p < .05), after controlling for age, gender, ethnicity, and socioeconomic status. The increased risk was uniform across diabetes subtypes. Among people with diabetes, common mental disorders were significantly associated with impaired health-related quality of life, more days off work, nonadherence, and difficulties with diabetes self-care.

Conclusions: People with diabetes are more likely to suffer from common mental disorders, a finding which is highly relevant, given that psychiatric comorbidity in people with diabetes is also associated with higher levels of functional impairment, impaired quality of life, and difficulties with diabetes self-care.

Key Words: diabetes • depression • anxiety • disability • diabetes self-care

Abbreviations: UK NPMS = United Kingdom National Psychiatric Morbidity Survey; ICD-10 = International Classification of Diseases-10; CIS-R = Clinical Interview Schedule-Revised; OCD = obsessive compulsive disorder; GAD = generalized anxiety disorder; MADD = mixed anxiety and depression disorder; ADLs = activities of daily living; SF-12 = Short Form-12 (Health-Related Quality of Life).


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESEARCH DESIGN AND METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Diabetes has been described by the World Health Organization as a "growing epidemic" with 150 million cases estimated currently, and 300 million cases estimated worldwide by 2025 (1,2).

Numerous descriptive studies have demonstrated that patients with diabetes have a two- to three-fold increased prevalence of depressive disorders (3,4). Many studies have used self-report tools to screen for depressive illnesses, which may lead to a higher prevalence of reported symptoms (3–7). Many of these studies have also been set in hospital clinics, which tend to over-select complicated patients (3–7). Anxiety disorders have been examined less frequently in people with diabetes, and most of these studies have also tended to draw their samples from hospital clinics (5,8), with a few exceptions (9). In addition, most previous work examining the associations of common mental disorders in people with diabetes and poorer self-care, disability, and service use, have focused on depressive disorders and have tended not to screen or analyze associations for other psychiatric comorbidities such as anxiety disorders.

Comorbidity between diabetes and common mental disorders is important because of the implications for chronic disease management and its potential impact on outcomes. People who suffer from both diabetes and depressive or anxiety disorders have less adequate glycemic control (10–12), more diabetic complications (13), increased service use, and lower medication adherence (11,13–15). Previous research has also demonstrated the adverse impact of comorbid depression on quality of life and disability in diabetes (16–18). Such associations may be confounded by other factors associated with common mental disorders in diabetes. Earlier population-based studies have found that female gender, younger age, lower education, and lower income are associated with an increased likelihood of depression in people with diabetes (19–22). An ongoing criticism of much work conducted to date has been the relative lack of control of potential covariates, owing to smaller sample sizes (3,5,6)

Therefore, in the present study, using a nationally representative sample of 8580 people aged 16 to 74 years, we conducted an analysis of the prevalence and association of diabetes and common mental disorders diagnosed by a structured interview, taking into account a wide range of potential covariates. We were interested in investigating a number of hypotheses. a) Is the prevalence of common mental disorders, determined by a structured diagnostic instrument (23) (including an assessment of International Classification of Diseases-10 (ICD-10) depression, anxiety, and comorbid anxiety depression as well as mixed anxiety and depression disorder (MADD) (24)) increased in a British population-based sample of people with diabetes, compared with a sample of people without diabetes, when important covariates such as age, gender, socioeconomic status, and ethnicity are taken into account? b) Which covariates (e.g., physical disability, marital support, stressful life events) are specifically associated with comorbid psychiatric morbidity in people with diabetes, in a community (as opposed to hospital) selected sample? c) Is the presence of comorbid common mental disorders in people with diabetes associated with poorer diabetes self-care and medication compliance, more working days lost due to illness, increased service use, and poorer quality of life, when compared with those people with diabetes who are not suffering from comorbid common mental disorders?


   RESEARCH DESIGN AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Study Setting and Sample
The most recent National Psychiatric Morbidity Survey in Great Britain (UK NPMS) was carried out between March and September 2000 (25). The survey included adults aged 16 to 74 years who lived in private households in England, Scotland, and Wales. The primary sampling units were 438 small area units selected from the national Postcode Address File, stratified by region and socioeconomic group. Households were systematically selected from each sector, and one eligible person was selected at random per household by the Kish Grid method (26). Trained lay interviewers carried out face-to-face computer-assisted structured interviews on 8580 individuals, with a response rate of 70%. The survey methodology details have been published elsewhere (25).

Measures
Demographic Variables
Interviewers asked study respondents basic questions about their sociodemographic background, such as age, gender, and occupational status. If the respondents were not working at the time of interview, this information was recorded as "economically inactive." For ethnicity, respondents were given a list of nine ethnicity categories as used in previous British Census surveys, and they asked to identify which ethnic group they belonged to.

Psychiatric Morbidity
The revised version of the Clinical Interview Schedule (CIS-R) (23) was used to measure common mental disorders. The CIS-R consists of subsections representing 14 symptom clusters. Questions are asked about the presence of symptoms and symptom severity in the previous month, with further questions focusing on the frequency and duration of symptoms in the previous week. Symptoms within each cluster are summed to create an overall psychological morbidity score. Additional questions enable ICD-10 diagnostic criteria (24) to be applied using computerized algorithms. Six diagnostic categories were obtained: obsessive-compulsive disorder (OCD), generalized anxiety disorder (GAD), depressive episode, phobias, panic and MADD (24). For the purpose of our analyses, these categories were divided into the following subcategories: a) Depression; b) Anxiety (OCD, GAD, panic, or phobia); c) Comorbid anxiety and depression; and d) MADD. For the purposes of this analysis, the "comorbid" category was considered present when a diagnosis of depression, as well as one of the anxiety disorders (excluding MADD), were present together.

The outcome of any "common mental disorders" included all those in any of these four (i.e., Depression, Anxiety, Comorbid Anxiety and Depression, MADD) mutually exclusive categories.

How CIS-R Derived (ICD-10) Diagnoses Approximates to DSM-IV Diagnoses
Over the evolution of the two diagnostic systems, Diagnostic and Statistical Manual of Mental Disorders-4th Edition (DSM-IV) (27) and ICD-10 (24), efforts have been made to keep the two systems compatible. Therefore, depression as determined by the CIS-R in this study (i.e., equivalent to ICD-10 diagnoses) should be seen as concordant with DSM-IV major depressive episode (24,27). Both ICD-10 and DSM-IV stipulate the presence of core depressive symptoms for at least 2 weeks with significant associated impairment in functioning, and this was incorporated into the algorithm for CIS-R "depressive episode." For our study purposes, mild, moderate, and severe depressive episode, as determined by CIS-R, were grouped together as "depression." Conversely, MADD was deemed present if respondents scored >12 on the CIS-R; however, they did not meet the criteria for any other common mental disorder diagnosis. This CIS-R algorithm for the diagnosis of MADD approximates the ICD-10 description of MADD, i.e., "symptoms of both anxiety and depression are present but neither set of symptoms considered separately is sufficiently severe to justify a diagnosis" (24), and symptoms needed to be present for a month. However, ICD-10 is less restrictive than the equivalent DSM-IV criteria for MADD (27). Both ICD-10 and DSM-IV-defined "MADD" is considered present if anxiety and depressive symptoms are present but only at "sub-threshold" levels, and not at levels whereby a separate diagnosis of anxiety or depression would normally be made (24,27). Dysthymia was not screened for in this study. Generalized anxiety disorder was considered present if symptoms of a) free-floating anxiety, b) autonomic over activity, and c) significant anxiety symptoms had been present for at least 6 months.Dysthymia was not screened for in this study. This ICD-10 algorithm-derived definition therefore also approximated closely that of the DSM-IV description of GAD, although DSM-IV GAD differs from ICD-10 GAD in also specifying symptoms of uncontrollability, focusing more on symptoms of hypervigilance and a stipulation around "clinical significance" (28). OCD was considered present if a) respondents reported significant obsessive and/or compulsive symptoms, associated with social impairment; b) had attempted to resist at least one act or thought; and c) had suffered this for ≥2 weeks (29). Phobias, which were screened for in this study, included agoraphobia with/without panic disorder, social phobia, and specific isolated phobia. In all of these cases, there had to have been evidence of significant social impairment, relevant and prominent avoidant behavior, and significant phobic behaviors associated with the phobia-specific situation (29). "Pure" panic disorder was considered present if a) the criteria for a phobic disorder were not met; b) respondents reported significant panic symptoms with evidence of recent panic attacks; and c) respondents also reported that they remained symptom-free between attacks (29).

Diabetes and Other Physical Illnesses
All participants were asked about the presence of any long-standing illness, disability, or infirmity. Interviewers coded responses using ICD-10 (24). Prescribed medication was also recorded and confirmed by interviewers checking the medication’s label. Diabetes was defined as present on the basis of self-reported diagnosis, and/or reported use of insulin or oral hypoglycemic medication. Prescribed medications were used to determine the "subtype" of diabetes; i.e., "prescribed-insulin," "prescribed oral hypoglycemics," or"not prescribed any medication but reporting presence of diabetes." Other physical illnesses aside from diabetes were also encoded.

Stressful Life Events, Health-Related Quality of Life, and Health Service Utilization
We used the brief life events questionnaire, a well-validated and reliable scale, which inquires after 12 stressful life events experienced by respondents within the previous 6 months (30,31). The UK NPMS also included a 7-item activities of daily living (ADLs) scale, used in previous national surveys (32). The seven questions about ADLs were: difficulties with bathing/personal care, difficulties using public transport, difficulties with medical care such as taking medicines/having injections, difficulties with household activities, difficulties with practical activities, difficulties in dealing with paperwork, and difficulties in managing finances. The Short Form Health-Related Quality-of-Life questionnaire (SF-12) was also used (33). Employment status was recorded. Those in employment were asked about days taken off work due to illness in the previous year.

Questions specific to diabetes care were also asked. Respondents were asked:

1) Do you sometimes not take your (diabetic medication) even though you should?
2) Do you have any difficulty with medical care such as taking medicines or pills, having injections or changes of dressing?
3) During the past year, have you been in the hospital as an inpatient, overnight, or longer for treatment or tests?
4) In the past 12 months, have you spoken to a family doctor on your own behalf either in person or by telephone about a physical illness or complaint?

Responses to questions were coded in a binary yes/no format.

Statistical Analyses
All analyses were weighted using STATA software to allow for the stratified, clustered sampling techniques and survey nonresponse (34). Given the multistage stratified sampling design, the data were weighted to consider differing selection probabilities and nonresponse using poststratification. All estimates of prevalence and association were made using the appropriate STATA survey commands to generate robust standard errors.

We first compared the sociodemographic characteristics of diabetes subtypes, and then compared these factors between people suffering from diabetes and people without diabetes, using {chi}2 tests. Next, we estimated the prevalence of depressive diagnoses, anxiety diagnoses, comorbid anxiety and depression, MADD, and any common mental disorder, within the group of people with diabetes. We generated odds ratios (ORs) to summarize the association between diabetes and common mental disorder, first generating an unadjusted model and then generating a model adjusting for important covariates. Covariates adjusted for in the analysis were age, gender, ethnicity, and socioeconomic status. These variables were selected because previous work has suggested that they are associated both with the likelihood of developing diabetes as well as also independently associated with common mental disorders. Finally, to investigate the impact of disability on the association between diabetes and common mental disorders, accepting that this might be a causal pathway factor, a further logistic regression was performed, controlling for reported disability.

An additional set of logistic regression analyses was performed, limited to people with diabetes. In the initial analysis, covariates which independently predicted the presence of common mental disorders in people with diabetes were assessed. Next, the independent effect of common mental disorders on self-reported health status, health service use and medication adherence, and social and occupational functioning, after adjusting for age, gender, ethnicity, and socioeconomic status was assessed.

Model diagnostics were performed for each regression model. These included tests for goodness-of-fit using Cook’s deleted residual, the distribution of residuals, and the Hosmer-Lemeshow statistic. When using the Hosmer-Lemeshow statistic, a p > .05 indicates satisfactory fit.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
DISCUSSION
 NOTES
 REFERENCES
 
Sample Characteristics
Of the 8580 participants, 239 people identified themselves as suffering from diabetes; of these, 67 were taking insulin, 118 were taking oral hypoglycemic medication, and 54 were not on any medication. Three respondents who did not identify themselves as having diabetes were taking insulin, and an additional seven were on oral hypoglycemic medication. Thus, the total sample of people with diabetes totaled 249. Nine of the 67 respondents taking insulin also reported taking oral hypoglycemics; these individuals were grouped together with those taking insulin only. The weighted prevalence of all forms of diabetes was 2.7%, insulin-treated diabetes 0.8%, oral hypoglycemic-treated diabetes 1.3%, and no-treatment diabetes 0.5%, consistent with previous national data from Great Britain (35,36).

Table 1 illustrates the sociodemographic characteristics of the sample. People with diabetes were more likely to be older, male, unemployed or economically inactive, left school before age 16 years, and be of manual occupational status. They resembled the rest of the population with respect to ethnicity and home ownership. People prescribed insulin were younger than those prescribed oral hypoglycemic medication or those who did not report receiving medication.


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  		TABLE 1. Demographic Composition of Total Sample

 

Diabetes, Common Mental Disorders, and the Impact of Covariates
A univariate analysis, comparing the subtypes of diabetes with those without diabetes with respect to the different categories of common mental disorder, was performed (Table 2). Within the diabetes subpopulation, a Wald test was performed for the null hypothesis of no heterogeneity in odds of common mental disorders between the three different diabetes subtypes. The p for the Wald F Statistic were: depressive diagnoses, p = .95; anxiety diagnoses, p = .27; MADD, p = .97; and any common mental disorder, p = .71. Therefore, the null hypotheses could not be rejected, indicating a lack of heterogeneity in risk for any of the categories of common mental disorders between diabetes subtypes. Therefore, in all subsequent analyses, diabetes subtypes were analyzed together. After controlling for age, gender, ethnicity, and socioeconomic status, people with diabetes were more likely to suffer from common mental disorders (OR = 1.5; 95% Confidence Interval (CI): 1.1–2.2).


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  		TABLE 2. Weighted Prevalence of Psychiatric Morbidity by Diabetes Status With Crude and Adjusted Odds Ratios for the Association Between Psychiatric Diagnoses and Diabetes

 

Diabetes, Common Mental Disorders, and Sociodemographic Factors
Among people with diabetes, common mental disorders were associated with female gender, life events in the past 6 months, comorbid physical illness, and disability (Table 3). Common mental disorders in this group were not significantly associated with education, occupation, or marital status. Overall, those from a minority ethnic group showed a nonsignificant trend for increased risk of common mental disorders compared with white people (OR = 2.2; 95% CI: 0.8–5.9); however, the numbers were small (Table 3).


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  		TABLE 3. Logistic Regression Models for Independent Variables Associated With Common Mental Disorders Among People With Diabetes

 

Association of Comorbid Common Mental Disorder With Health and Functioning in Diabetes
Table 4 summarizes health service use and health-related quality of life outcomes. Poor self-reported adherence and "difficulties with medical care" were associated with common mental disorder in diabetes (p < .05). Hospital admissions were more frequent among those with diabetes compared with people without diabetes, and this was independent of the presence of comorbid common mental disorders. However, the presence of common mental disorders was associated with increased consultation rates for physical disorder among people with diabetes (p < .05). People with diabetes with and without common mental disorders were equally likely to be unemployed or economically inactive. However, there were strong independent effects of common mental disorders on days taken off sick, pain interfering with work, and impaired physical functioning (p < .05).


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  		TABLE 4. Health Service and Health-Related Quality of Life Outcomes by Diabetes and Mental Health Status

 

Model Diagnostics
We examined plots of residual and leverage statistics, and no unusual findings for any of the models were observed. The Hosmer and Lemeshow statistic suggested satisfactory fit for all models, although the model for the association between diabetes and anxiety disorders when controlling for age, gender, socioeconomic status, and ethnicity did not fit perfectly (Hosmer and Lemeshow {chi}2 = 24.60; p = .0018). However, once impairment on ADLs was also included in this model (Table 2, Model 2); the Hosmer and Lemeshow Statistic demonstrated satisfactory fit (Hosmer and Lemeshow {chi}2 = 14.01; p = .0816).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 DISCUSSION
NOTES
 REFERENCES
 
This analysis from a large national population sample in Great Britain suggests that people with diabetes are 50% more likely to suffer from common mental disorders than people without diabetes. In a meta-analysis examining the association of diabetes with depression, Anderson et al. (3) found people with diabetes were twice as likely to suffer from depression compared with people without diabetes. The strength of association with diabetes was concluded to be higher in studies that used self-report instruments, because such instruments also detect subsyndromal presentations of depression or dysthymia as well as comorbid anxiety symptoms (3). In our study, with a fully structured clinical assessment, which approximated the ICD-10 diagnostic criteria, we were able to differentiate between depression, anxiety, comorbid depression and anxiety, and MADD. Our findings suggest that MADD is an important contributor to the burden of overall psychiatric comorbidity suffered by people with diabetes. There may be a significant association of subsyndromal psychological distress with diabetes because many of the problems that people with diabetes have relate to illness beliefs, self-efficacy, and adjusting to and living with a chronic illness (37).

One of the main advantages of the study compared with previous studies was the use of diagnostic interviews to screen for common mental disorders (3–6). In addition, the large sample size and population-based design of UK NPMS conferred several advantages. We were able to adjust for potential covariates, often not done adequately in previous studies due to small sample sizes (3,5). The population-based approach also meant that selection biases arising from using specialist service samples were minimized. The inclusion of a large sample of people without diabetes allowed for important comparisons to be made. Our study confirmed that the correlates of common mental disorders in diabetes seem similar to those for common mental disorders in general, and included the female gender and recent stressful life events. Some of these findings are in keeping with previous studies on people with diabetes (19–22,38). However, we found no significant associations between marital status, occupational status, or level of education, and common mental disorders. These differences in our findings compared with previous work may have been due to the smaller sample size of people with common mental disorders and diabetes in our study (n = 60) and should be interpreted with caution. Our findings also suggested a nonsignificant trend between nonwhite ethnicity of people with diabetes, and a potential association with an increased risk of common mental disorders.

An important finding was the presence of comorbid common mental disorders in participants with diabetes, and its association with several adverse features. Among people with diabetes, those with comorbid common mental disorders were more likely to report lower medication adherence, greater difficulties managing medical care, and more working days lost due to illness. The presence of common mental disorders in people with diabetes was also significantly associated with recent consultations with a family doctor over physical complaints as well as associated with more reported pain.

Much of the existing literature on common mental disorders in people with diabetes has been based on studies conducted in North America (19–22,38); however, the rates of diabetes are twice as high in Great Britain compared with the USA (39). In addition, differences in health service provision and potential differences in the social determinants of health between the two countries could have differing effects on overall health outcomes (39). It is noteworthy that the main finding of our study—namely, people with diabetes and comorbid common mental disorders report worse Health-Related Quality of Life and report greater difficulties with diabetes self-care (compared with those not suffering from comorbid common mental disorders)—is similar to those studies which had been conducted in North America (19–22,38).

Overall, the association between diabetes and common mental disorders was reduced to null after adjustment for ADLs impairment in the logistic regression analyses (Table 2, Model 2), suggesting that disability associated with diabetes could account for much of the association between diabetes and common mental disorders. A similar effect was seen, whereby the size of effect between diabetes and common mental disorders was reduced, when the presence of other comorbid physical illnesses was added in to the model. Both of these findings should be interpreted with caution, given the possibility of over adjustment in the regression analyses (40) and the awareness that people with depression may also be more likely to report ADLs impairment. However, our findings are also consistent with an earlier meta-analysis (13) reporting an association between diabetic complications (and presumably attendant disability) and depression as well as a more recent study which demonstrated that the presence of increasing physical comorbidity in people with diabetes was positively associated with an increased odds of depression (41). One implication is that interventions targeting common mental disorders in diabetes may need to not only prevent complications but also minimize consequent disability, handicap, and loss of role function.

As this was a cross-sectional dataset, it was also not possible to draw firm conclusions concerning the direction of causality. A limitation of the study was that a previous history of depression was not elicited, knowing this may have helped to further clarify potential directions of association between diabetes and depression. However, epidemiological tools that inquire about lifetime diagnoses of depression may be subject to recall biases (42,43), and so this would not have necessarily clarified the issue in our study, had it been asked. There is a body of literature which suggests that depression may precede diabetes, particularly Type 2 diabetes, by up to a decade (44–46). In addition, physical functioning, which may become impaired as the result of a comorbid physical illness such as diabetes, may also predispose to common mental disorders, and the association between depression and physical disability may be bidirectional (47,48). Disability may also be a direct 1:1 accompaniment of common mental disorders. To a certain extent, our findings complement those of another recent cross-sectional study where minor depressive illness and diabetic complications were associated with a two-fold increase in disability risk in people with diabetes (18). The benefits of treating comorbid depression in people with diabetes have been shown to have a direct impact in improving overall functional status (49).

There were some important limitations inherent in the design of this study. There may have been some misclassification of diabetes, and some of this may have been nonrandom with respect to common mental disorders outcome. However, although our measure of diabetes was based on self-report, this has been shown in previous work to be reasonably accurate, with an estimated sensitivity of 73%, and specificity of 99% (50–52). In addition, the recording of prescribed medications by the interviewers in our study further improved overall diabetes classification and allowed some categorization into diabetes subtypes. The prevalence figures in our study approximated closely the previously reported diabetes prevalence in Great Britain (35,36).

The use of the CIS-R in this study was advantageous as it was possible to differentiate between cases of "pure" ICD-10 depression or anxiety versus comorbid depression and anxiety. The diagnosis of "depression" as determined by this study approximates that of DSM-IV major depression, although one drawback was that the CIS-R did not screen for dysthymia, which may have been subdivided within the "depression" category, therefore potentially inflating the depression prevalence figure, in our study. However, it was possible to detect a subset of people within a "subthreshold" category of MADD, where the diagnostic criteria for depression or anxiety may not have been met but where there was still significant psychological distress or symptomatology. It is important to note that the category of MADD in this study differs from the more restrictive provisional criteria of Mixed Anxiety and Depressive Disorder in DSM-IV. Although this might mean that MADD might have been over diagnosed in this analysis, compared with studies using DSM-IV criteria, recent analyses suggest that MADD, as determined by these criteria, is associated with significant population-level morbidity comparable with "threshold" diagnoses such as depression or anxiety disorders (Das-Munshi et al., article in preparation).

There were several potential disadvantages of using the CIS-R. The CIS-R does not differentiate between recurrent and first episode presentations of depression. This could be a limitation as major depression tends to be a chronic or recurring illness in people who suffer from Type 2 diabetes (19). In addition, the CIS-R is a fully structured assessment administered by trained lay interviewers, and concerns have been expressed regarding the validity of such measures (53,54). However, more recently, work has shown that the CIS-R is reasonably valid in the assessment of common mental disorders, when measured against the "gold standard" of the Schedules for Clinical Assessment in Neuropsychiatry (SCAN), with a specificity of 97% and a sensitivity of 41% and a positive predictive value of 90%, when used to detect any ICD-10 diagnosis of common mental disorder (55). In this study, the area under the receiver operating characteristics curve (AUROC) was 0.87 (95% CI: 0.79–0.95), and demonstrated that the CIS-R showed good overall discriminability for ICD-10 common mental disorders, when compared with the SCAN (55). In addition, the {kappa} coefficient of reliability when comparing the CIS-R with the SCAN, when determining ICD-10 diagnoses at syndrome level, was found to be satisfactory ("any acute/chronic depression," {kappa} = 0.52 (95% CI: 0.31–0.73); "any anxiety disorder," {kappa} = 0.52 (95% CI: 0.34–0.70); "any ICD-10 diagnosis," {kappa} = 0.41 (95% CI: 0.25–0.57)) (55).

We did not examine the association of other chronic medical conditions with common mental disorders, as this was beyond the scope of the present analysis. As this was a population survey, the sample of people without diabetes who served as a control group would have contained people suffering from other chronic conditions. One would therefore expect the odds of association of diabetes with common mental disorders to have been greater, had the comparison group contained purely healthy controls with no other physical illnesses. Our analysis of physical comorbidity in people with diabetes suggested that, when this was grossly measured within the sample of people with diabetes, other physical illnesses were also important in mediating the association of diabetes with common mental disorders. Further work is needed to clarify if such an association is specific to people with diabetes or is applicable to other groups of people suffering from other chronic medical conditions, although work of this nature would be limited by attempting to compare illnesses of differing personal and functional impact.

We would like to thank Renata Sousa for help with retrieving data on comorbid physical disorders, and Michael Dewey for statistical advice. No funding has been received by any of the authors in carrying out this study.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 DISCUSSION
 NOTES
REFERENCES
 
Received for publication May 10, 2006; revision received March 29, 2007.

DOI:10.1097/PSY.0b013e3180cc3062


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 

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