DÄ internationalArchive23-24/2019Mortality and Medical Comorbidity in the Severely Mentally Ill

Original article

Mortality and Medical Comorbidity in the Severely Mentally Ill

A German registry study

Dtsch Arztebl Int 2019; 116: 405-11. DOI: 10.3238/arztebl.2019.0405

Schneider, F; Erhart, M; Hewer, W; Loeffler, L A; Jacobi, F

Background: Mentally ill patients die on average 10 years earlier than the general population, largely due to general medical disorders. This study is the first to explore in a large German sample the prevalence, mortality, and medical comorbidity in patients with severe mental illness (SMI). The patients were affected by borderline personality disorder (BPD), psychotic disorders, bipolar disorder, or severe unipolar depression.

Methods: Our database consists of billing data from all adults with statutory health insurance in Germany. Twelve-month administrative SMI prevalence and medical comorbidity were estimated using cross-sectional data from 2016 (age ≥ 18; N = 59 561 310). Two-year mortality was established longitudinally in a randomly selected subset of the billing data (most recent mortality information available for 2012 to 2014; 2012: n = 15 590 107).

Results: Severe unipolar depression had the highest prevalence (2.01%), followed by psychotic disorders (1.25%), BPD (0.34%), and bipolar disorder (0.29%). While the prevalence of malignant neoplasms showed moderate deviations from reference values [severe unipolar depression: OR = 1.30 (95% CI = 1.29; 1.31), BPD: OR = 1.11 (1.09; 1.14), psychotic disorders: OR = 0.90 (0.89; 0.90), bipolar disorder: OR = 1.07 (1.06; 1.09)], other disease groups (infectious, endocrine/nutritional/metabolic, circulatory, respiratory) were substantially elevated in all categories of SMI. Mortality rates for psychotic disorders, BPD, bipolar disorder, and severe unipolar depression were increased (OR = 2.38 [95% CI=2.32; 2.44], 2.30 [2.08; 2.54], 1.52 [1.42; 1.62], and 1.40 [1.37; 1.44], respectively), with a loss of 2.6 to 12.3 years, depending on age, sex, and SMI.

Conclusion: Mortality is substantially elevated in all SMI patients. The results underline the need to remove barriers to adequate general medical care, both on the patient and the provider side, to reduce excess mortality.

LNSLNS

Extensive research has shown increased mortality among patients with mental disorders, especially in those affected by severe mental illness (SMI) (1, 2), which typically includes schizophrenia and uni-/bipolar depression (24, e1).

In a recent meta-analysis, Walker and colleagues (5) revealed that mortality in mentally ill patients is more than twice as high as in the general population, with two third of the deaths being due to natural causes. In total, an estimated 8 million deaths worldwide (14.3%) are due to mental disorders every year and the reduction in life span is estimated at 10 years (median) (5). Some authors have described even greater shortening of life, between 13 and 30 years (6, 7). In Germany, the number of seriously mentally ill adults is estimated at 1–2% of the population, i.e., up to 1 million affected individuals (8). The global burden of mental disorders is a serious public health problem (9, 10). Alongside unnatural causes of death such as accidents and suicide, the increased number of premature deaths is largely attributable to physical illness such as cardiovascular disease and endocrine and metabolic disorders (3, e1). Cardiovascular disease is the leading cause of death in the general German population (11).

Research on mortality and medical morbidity in SMI usually focuses on schizophrenia, bipolar disorder, and severe depression. Borderline personality disorder (BPD) is also a clinically severe mental illness but has rarely been studied with regard to mortality and medical morbidity.

To extend the research findings to BPD, we conducted the first population-based registry study using adult data from all statutory health insurance funds in Germany, representing a very large collective (age ≥ 18; N = 59 561 310). Previously, no such study could be conducted in Germany, a country with some of the strictest data protection regulations in the world (12), and until recently no national claims data composed of persons insured by all statutory health insurance funds were available for such analyses. Since BPD has not been included in this context before, in Germany or elsewhere, the present study makes a unique contribution to the understanding of comorbidity and mortality in SMI.

We set out to quantify:

  • Medical comorbidity and risk factors in SMIs, including BPD.
  • (Increased) mortality in SMI patients and estimated reduction in life span.

Additionally, 12-month SMI prevalences in Germany were determined.

Methods

Datasets and study types

The database consists of billing data (§ 295 German Social Code V) from all adults with statutory health insurance who had contact with general or specialist physicians or psychotherapists accredited to invoice the German regional associations of statutory health insurance physicians (ASHIP) (13).

Twelve-month prevalence and medical comorbidity of SMI patients were examined cross-sectionally using the latest available billing data (2016: age ≥ 18 years; N = 59 561 310). Patients who had no contact with the health system in 2016 were not included in the analyses.

The dataset from 2016 lacks information on mortality. Using the most recent data available, 2-year mortality was calculated longitudinally for the years 2013 and 2014 for patients with and without a SMI diagnosis in 2012 (2012: n = 15 590 107).

Diagnostic assessment

Psychiatric diagnoses were operationalized using routine diagnoses (coded according to ICD-10) assigned by medical service providers to the (same) patient. Based on previous research (14) and relevance for psychiatric health care (e2), we included BPD (F60.3x), psychotic disorders (schizophrenia, schizotypal and delusional disorders, F2x), bipolar affective disorder (F31.x, including manic episode, F30.x), and severe unipolar depression (F32.2/33.2, F32.3/F33.3; eMethods).

Based on clinical and theoretical considerations, a selected range of general medical conditions were specified according to ICD-10 code and relevant risk factors of mortality and included in comorbidity analyses (eTable 1).

Ethical standards

The local ethics committee of the Faculty of Medicine, RWTH Aachen University, raised no ethical or professional objections to the research project.

Statistical analyses

We present 12-month administrative prevalences for the year 2016. Odds ratios (OR) of the medical conditions and risk factors (adjusted for age group [18–24, 25–34, 35–44, 45–54, 55–59, 60–64, 65–69, 70–74, 75–79, 80–84, 85–89, 90–94, 95+] and sex, inclusive interaction) were calculated by means of multiple logistic regression and separated for six subgroups (three age groups [18–39, 40–64, 65+] × sex).

In order to evaluate whether significant ORs were also substantial in terms of effect size, we selected the established cut-offs originally proposed by Chinn (15): OR >1.436 and OR <0.696. Base rates of all medical diagnoses are provided to enhance interpretation of ORs (eTable 1).

Mortality rates for 2013 to 2014 were calculated as a raw percentage for patients with and without a diagnosis of SMI in 2012. OR were calculated according to the Mantel–Haenszel (OR-MH) method to account for variation in OR across age and sex groups (16). The OR indicate increased mortality of patients with a specific SMI compared with patients without that SMI. Due to the low prevalence of mortality rates, the OR resemble relative risks (RR).

Loss of life years was estimated using statistical life tables for the general German population in 2014 (eMethods) (17). The difference in life expectancy between the total population and a particular SMI population was taken as proxy for lost life years.

Results

Twelve-month prevalence

Severe unipolar depression had the highest 12-month prevalence (2.009%; n = 1 196 710), followed by psychotic disorders (1.245%; n = 741 528), BPD (0.341%; n = 203 378), and bipolar disorder (0.288%; n = 171 494; Table 1). BPD prevalence dropped with age, while other SMIs showed a rise after the age of 40 years and then remained relatively stable. Prevalence was higher in women than in men.

Administrative prevalences (2016) of borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression by age and sex*1
Administrative prevalences (2016) of borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression by age and sex*1
Table 1
Administrative prevalences (2016) of borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression by age and sex*1

Medical comorbidity

The greatest effects (eTable 1) were found for relevant risk factors, external causes of morbidity/mortality (e.g., intentional self-harm, substance use disorders), and neurodegenerative diseases. While malignant neoplasms were particularly prevalent in severe unipolar depression, other disease groups (infectious/parasitic, endocrine/nutritional/metabolic, circulatory, and respiratory diseases) were substantially elevated in all SMIs, especially in BPD.

There were no substantial decreases in comorbidities or risk factors (OR <0.696), but a significant effect was found for psychotic disorders with regard to malignant neoplasms (OR = 0.90; eTable1).

Mortality and life years lost

In total, 288 503 patients from the 2012 sample died in 2013 or 2014. Across age and sex, BPD was associated with a 2.30-fold (95% CI [2.08; 2.54]) increase in mortality rate within this two-year period compared with patients without BPD. Two-year mortality rates for psychotic disorders, bipolar disorder, and severe unipolar depression were increased by factors of 2.38 (2.32; 2.44), 1.52 (1.42; 1.62), and 1.40 (1.37; 1.44), respectively (Table 2, eTable 2).

Increased 2-year mortality rates in men and women with and without borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression*1
Increased 2-year mortality rates in men and women with and without borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression*1
Table 2
Increased 2-year mortality rates in men and women with and without borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression*1

Figure 1 shows the relative risk of death over the whole life span between SMI patients and patients without the given SMI (ratio). The elevation in mortality among SMI patients was greatest at young age (particularly in psychotic disorders: 11-fold), where the annual risk of death is low (<0.1% in the general population). In old age (e.g., 85 years), where the general annual risk is high (around 16%), BPD, psychotic disorders, bipolar disorder, and severe unipolar depression still showed statistically significantly elevated mortality rates (RR = 1.78 (95% CI = 1.34; 2.36), 1.66 (1.57; 1.75), 1.25 (1.04; 1.49), 1.21 (1.14; 1.29); eFigure 1) (18).

Mortality rates in patients with severe mental illness (SMI) compared with patients without the respective SMI (relative risk) over the whole adult life span
Mortality rates in patients with severe mental illness (SMI) compared with patients without the respective SMI (relative risk) over the whole adult life span
Figure 1
Mortality rates in patients with severe mental illness (SMI) compared with patients without the respective SMI (relative risk) over the whole adult life span
Age-dependent mortality in patients with SMI and in patients without the specific SMI, together with the relative risk (SMI vs. no SMI) over the whole adult life span
Age-dependent mortality in patients with SMI and in patients without the specific SMI, together with the relative risk (SMI vs. no SMI) over the whole adult life span
eFigure
Age-dependent mortality in patients with SMI and in patients without the specific SMI, together with the relative risk (SMI vs. no SMI) over the whole adult life span

The estimated loss of life years for SMI patients was greatest in psychotic disorders (ranging from 8.2 years [age 50] to 11.5 years [age 20]), followed by BPD (5.7 years [age 50] to 7.1 years [age 20]); higher in younger than in older patients; and more pronounced in men than in women (Figure 2, eTable 3).

Estimated loss of life years by age for patients with severe mental illness (SMI) compared with total population
Estimated loss of life years by age for patients with severe mental illness (SMI) compared with total population
Figure 2
Estimated loss of life years by age for patients with severe mental illness (SMI) compared with total population
Estimated loss of life years by age in SMI patients compared with the total population (administrative data of all statutory health insured adults in Germany, age = 18 years*1, 2013 to 2014)
Estimated loss of life years by age in SMI patients compared with the total population (administrative data of all statutory health insured adults in Germany, age = 18 years*1, 2013 to 2014)
eTable 3
Estimated loss of life years by age in SMI patients compared with the total population (administrative data of all statutory health insured adults in Germany, age = 18 years*1, 2013 to 2014)

Discussion

The present study focused on excess mortality and medical comorbidity in people with severe mental illness (SMI), a highly relevant topic with regard to sociopolitical equity and health care participation (19). Analyses of SMI comorbidity revealed many clinically significant associations contributing to excess mortality due to natural causes.

Besides HIV and hepatitis, elevated medical comorbidities included obesity, diabetes, cardiac and cerebrovascular disease, chronic obstructive pulmonary disease, pneumonia, and some cancers. Furthermore, the risk of death was markedly elevated in SMI—including BPD—and associated with a substantial loss of life years.

Although the risk of suicide is highly elevated in SMI patients, the excess mortality can mainly be attributed to somatic causes. According to official statistics for the period 2013 to 2014, in Germany around 1.2% of all deaths are documented as suicides (18).

Based on the assumption from previous findings that up to 90% of completed suicides are associated with mental disorders in general (5, 20, 21), we estimated that the SMIs included in our study (which are more severe but less prevalent) accounted for 70% ofcompleted suicides. Thus, our data suggest that 24% of SMI excess mortality per year can be attributed to suicide and 76% to somatic causes (i.e., medical morbidity) or other, unnatural causes (eMethods). In part our findings replicate long-standing data on poor medical health in people with SMI (15), and our results suggest good external validity of the data.

Nonetheless, compared with recent reviews, excess mortality seems relatively low, although within the range of most studies. One reason might be that the German social and healthcare systems offer relatively good free general access to mental and medical care. Furthermore, our prevalence estimates are conservative, since SMI patients with zero contact to the health care system are not represented.

The statutory health insurance database is unique in covering the majority of SMI patients in Germany. The proportion of SMI can be assumed to be lower in the privately insured population than in those with statutory insurance (22). Moreover, routine data are not affected by selection bias with regard to recruitment or participants’ willingness to participate in a study.

Nevertheless, routine records and thus administrative prevalences are usually less valid than datasets based on standardized diagnostic procedures (23, e3). The inclusion of only severely ill patients in the current study contributes to higher validity of the diagnoses. As a consequence, however, the findings may not be generalizable to less severe disease courses. Furthermore, we must assume that the true SMI prevalence is higher than reported here due to patient- and healthcare system-related factors such as underutilization, nonrecognition, undertreatment, stigmatization, and inadequate mental health services in certain regions (24).

Our prevalence rates of bipolar disorder are lower than reported in previous clinical or epidemiological field studies (e.g., 0.8% for any bipolar disorder [23]). This may reflect flawed sensitivity (unrecognized cases) and specificity (e.g., diagnosis of unipolar depression or schizoaffective disorder diagnosis instead of bipolar disorder) in routine care, as well as the episodic nature of (hypo-)manic symptoms (i.e., many lifelong illnesses are not coded in every 12-month period). However, we do not believe that the low prevalence rates affect the reported associations between bipolar disorders and medical comorbidities or mortality.

Potential flaws in SMI diagnostics may impair the validity of associations of SMI with medical comorbidity and mortality: Underdiagnosis, for example, leads to underestimation of association effects in patients who make use of healthcare services. However, in patients who do not use these services, underdiagnosis contributes to neither overestimation nor underestimation of associations. Counterintuitive findings such as lower medical comorbidity (e.g., disorders of lipoprotein metabolism, cardiac arrhythmia) in psychotic disorders than in other SMIs, despite the fact that this group has the highest mortality rates, may be due to underrecognition and undertreatment (25, e3). Assuming that this bias applies to SMI patients in general, medical comorbidity—but not mortality—may be under-estimated.

It is conventional to define SMI on the basis of specific coded diagnoses (26) but one should not neglect the fact that other mental disorders can also be associated with severe distress, role impairment, and disability.

Considering the lack of direct measures of severity (e.g., a score ≤ 50 on the Global Assessment of Functioning scale [27]), we believe that our diagnosis-based approach (including the addition of BPD to conventional SMIs) is the most feasible way to address medical comorbidity and mortality in patients with SMI.

The dataset does not include information on:

  • Privately insured or self-funding patients
  • (Pre-/semi-) inpatient care
  • Psychiatric hospital/university outpatient services
  • Medical/occupational rehabilitation
  • Remedies and appliances
  • Socioeconomic variables and family background.

Since SMIs are very probably less prevalent in privately insured patients (no statistics available), the findings of the present study are representative only for patients with statutory health insurance (22).

Patients who (within a given year) visit only psychiatric hospital outpatient services before or after hospitalization and patients with exclusively long hospitalizations are not coded in the present billing data. However, it can be assumed that these patients also have at least one contact per year with other psychiatric/general healthcare facilities and thus were not lost in our dataset.

Outlook and implications for care

Medical comorbidity and mortality in the mentally ill are increased by an accumulation of health risks caused, for instance, by socioeconomic problems (e.g., unemployment, poverty, social isolation, imprisonment, homelessness) and associated lifestyle factors (e.g., smoking, alcohol/drug use, poor nutrition, obesity, physical inactivity, unprotected sex, psychological trauma). At the same time, people with chronic mental disorders are on the margins of normal medical care: they use health services only to a limited extent, and there are indications of poor compliance by this group of patients (3, 40).

Focusing on mental health problems often prevents care providers from dealing constructively with the medical illness. Furthermore, for various reasons the principles of inclusion and equity are not guaranteed for this patient group in the medical sector (28).

Other factors related to the communication between doctor and patient may also be relevant. Physicians frequently attribute a patient’s symptoms to his or her mental disorder when they are actually related to a general medical condition. Alternatively, physicians may ignore physical health in the presence of prominent psychiatric symptoms (‘diagnostic overshadowing’) (29, e4). Here, models of collaborative care show promising effects (3032). Many risk factors for “natural causes of death” (e.g., obesity) can be influenced (6, 3335, e5), which emphasizes the need for further investigation of interventions to reduce mortality in SMI. In this context, effective treatment strategies for patients with comorbid substance use disorders might be crucial, as increased mortality is likely to be caused to a considerable extent by related physical illness (4).

Furthermore, although psychotropic drugs significantly reduce mortality overall, they can have adverse effects that promote the occurrence of medical comorbidities (36, 37). Examples are (38, e2):

  • Diabetes and subsequent metabolic syndrome
  • Increased cardiovascular mortality caused by pronounced weight gain as an adverse effect of many atypical antipsychotics
  • Increased cardiovascular morbidity and mortality caused by many psychotropic drugs with anticholinergic effects, such as antidepressants and antipsychotics
  • Severe arrhythmias caused by pharmacologically induced QT prolongation

Thus, the pharmacological management of medical illness has to be specifically tailored to SMI patients.

In conclusion, the need for health-promoting interventions is beyond question and should be reflected in all treatment guidelines regarding SMI (39).

Acknowledgments

We thank Jessica Junger, PhD and Mandy Schulz, PhD for assistance and Dominik Graf von Stillfried, PhD and Frank Bergmann, MD for support. Furthermore, we are very grateful to Michael Deuschle, MD, Hans Grabe, MD, Ralf-Dieter Hilgers, PhD, and Steffi Riedel-Heller, MD for their comments on earlier drafts.

Funding

The work of Frank Jacobi on the present study was supported by the German Association for Psychiatry, Psychotherapy and Psychosomatics (DGPPN).

Conflict of interest

All authors declare that no conflict of interest exists.


Manuscript received on 4 September 2018, revised version accepted on 27 March 2019

Correspondence to:

Prof. Frank Schneider, M.D., Ph.D.,

University Hospital Düsseldorf,

Moorenstr. 5, 40225 Düsseldorf, Germany

E-mail: frank.schneider@med.uni-duesseldorf.de,

Cite this as:
Schneider F, Erhart M, Hewer W, Loeffler LAK, Jacobi F: Mortality and medical comorbidity in the severely mentally ill—a German registry study. Dtsch Arztebl Int 2019; 116: 405–11. DOI: 10.3238/arztebl.2019.0405

Supplementary material:
For eReferences please refer to:
www.aerzteblatt-international.de/ref2319

eMethods, eTables, eFigures:
www.aerzteblatt-international.de/19m0405

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* Joint first authors
University Hospital Düsseldorf: Prof. Dr. med. Dr. rer. soc. Frank Schneider
Central Institute for Ambulatory Care in Germany, Berlin, Germany: Prof. Dr. P. H. Michael Erhart
Alice Salomon University Berlin, Germany: Prof. Dr. P. H. Michael Erhart
Department of Geriatric Psychiatry, Christophsbad Hospital, Göppingen, Germany: Prof. Dr. med. Walter Hewer
Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, Aachen, Germany: Prof. Dr. med. Dr. rer. soc. Frank Schneider, Leonie AK Loeffler, M. Sc.
Psychologische Hochschule Berlin, Berlin, Germany: Prof. Dr. rer. nat. habil. Frank Jacobi
Mortality rates in patients with severe mental illness (SMI) compared with patients without the respective SMI (relative risk) over the whole adult life span
Mortality rates in patients with severe mental illness (SMI) compared with patients without the respective SMI (relative risk) over the whole adult life span
Figure 1
Mortality rates in patients with severe mental illness (SMI) compared with patients without the respective SMI (relative risk) over the whole adult life span
Estimated loss of life years by age for patients with severe mental illness (SMI) compared with total population
Estimated loss of life years by age for patients with severe mental illness (SMI) compared with total population
Figure 2
Estimated loss of life years by age for patients with severe mental illness (SMI) compared with total population
Key messages
Administrative prevalences (2016) of borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression by age and sex*1
Administrative prevalences (2016) of borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression by age and sex*1
Table 1
Administrative prevalences (2016) of borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression by age and sex*1
Increased 2-year mortality rates in men and women with and without borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression*1
Increased 2-year mortality rates in men and women with and without borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression*1
Table 2
Increased 2-year mortality rates in men and women with and without borderline personality disorder, psychotic disorders, bipolar disorder, and severe unipolar depression*1
Age-dependent mortality in patients with SMI and in patients without the specific SMI, together with the relative risk (SMI vs. no SMI) over the whole adult life span
Age-dependent mortality in patients with SMI and in patients without the specific SMI, together with the relative risk (SMI vs. no SMI) over the whole adult life span
eFigure
Age-dependent mortality in patients with SMI and in patients without the specific SMI, together with the relative risk (SMI vs. no SMI) over the whole adult life span
Estimated loss of life years by age in SMI patients compared with the total population (administrative data of all statutory health insured adults in Germany, age = 18 years*1, 2013 to 2014)
Estimated loss of life years by age in SMI patients compared with the total population (administrative data of all statutory health insured adults in Germany, age = 18 years*1, 2013 to 2014)
eTable 3
Estimated loss of life years by age in SMI patients compared with the total population (administrative data of all statutory health insured adults in Germany, age = 18 years*1, 2013 to 2014)
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