Diabetes and mental illness are major causes of disability and mortality and consume a significant aspect of the Australian health budget (1, 2). The age-standardized prevalence of type 2 diabetes in Australia has doubled over the last decade according to the Australian Institute of Health and Welfare Data, with 4.2% of population having diabetes between 2011 and 2012 compared to 1.5% in 1989–90 (3). We recently showed that approximately one-third of general inpatients aged >54 years admitted to our hospital had type 2 diabetes (4). A recent Melbourne Public Hospitals Diabetes Inpatient Audit revealed the prevalence of diabetes ranged from 16 to 35% in different hospitals across the greater metropolitan region (5).

Likewise, the prevalence and effects of mental illness are many-fold. Many Australians experience mental illness at some point in their lives (6). In a large Australian survey of approximately 1,800 community-dwelling people with psychotic illness, approximately 20% had diabetes (6). This is a concern, given the relative youth of people affected by both diabetes and psychosis (~88% were aged less than 55 years) and that the age-matched prevalence of type 2 diabetes in the community at 55 years was only 8% (3). The survey examined patients with psychotic disorders in the community, and there are limited data in the inpatient setting. Furthermore, the survey did not delineate additional clinical characteristics in the cohort of patients with diabetes (6). There are no Australian data on the prevalence of diabetes and pre-diabetes in psychiatry inpatients.

Psychiatry inpatients are likely to be more vulnerable to diabetes, largely because of the acuity of the mental illness as well as the likelihood they will be exposed to higher doses or multiple medications that increase diabetes risk (6).

Diabetes and mental illness share a bidirectional interface where both influence each other (7, 8). This is important to appreciate when trying to understand the underlying pathophysiology and characteristics of patients who might be at increased risk. Many studies have shown a link between antipsychotic medication and impaired glycemia. A systematic review and meta-analysis undertaken in 2008 examined 11 studies to date (9). It demonstrated that the relative risk of diabetes in patients with schizophrenia prescribed second-generation versus first-generation antipsychotics was 1.32 (95% CI 1.15–1.51) (9). However, this observation is likely to be biased due to the methodological limitations in many of the studies included (9).

Measuring hemoglobin A1c (HbA1c) as a means of identifying patients with diabetes is now recommended by the American Diabetes Association (ADA), as it is considered to be a more stable parameter, less affected by factors, such as fasting status, glucocorticoid use, or stress hyperglycemia (10, 11). In a small study of people with mental illness treated with antipsychotic medications in the community, HbA1c measurements detected a greater number of cases with pre- diabetes or diabetes, compared with the use of the fasting blood glucose criteria (12). Little has been documented about the use of HbA1c in the inpatient population with severe mental illness.

Using routine HbA1c testing, the aim of this study was, therefore, to determine the prevalence, characteristics, and length of stay (LOS) of psychiatry inpatients with diabetes compared to those with pre-diabetes or without diabetes.

All patients admitted to the inpatient psychiatry unit at Austin Health, a major tertiary hospital, affiliated with the University of Melbourne, during the study period (February 2014 to April 2015) above the age of 30 were included in this prospective observational study. During the 14-month study period, all inpatients underwent HbA1c testing on admission via Cerner Millennium Information System Program, as part of routine clinical care as part of the Diabetes Discovery Initiative (4). Cerner Millennium Information System Program is the electronic health system used at Austin Health. We wrote a “discern rule” to identify all inpatient admissions with the following eligibility criteria: age ≥ 30 years, acute psychiatric unit admission, and no HbA1c recorded within 3 months. If these criteria were satisfied, an automatic request for HbA1c was generated for routine blood collection. All HbA1c results were reported via Cerner and were accessible to the patients’ treating clinicians. As part of the Diabetes Discovery Initiative, all inpatients with HbA1c ≥ 8.5% (69 mmol/mol) were automatically reviewed by the endocrinology team to intensify diabetes treatment, screen for complications, and optimize management (4). A paragraph describing the HbA1c result and its interpretation was automatically inserted into each discharge summary to patients’ local doctors (4).

Baseline characteristics, including demographic data such as age, sex, residence, marital status, employment, drug, and alcohol history were collected. Information regarding comorbidities was obtained from each patient’s medical record to calculate the Charlson Index score without diabetes. This validated method of weighting the impact of chronic disease, assigns each chronic condition a score of 1, 2, 3, or 6, depending on severity and impact on mortality (4). Specific comorbidities, including diabetes, hypertension, obesity (using weight and body mass index), and dyslipidemia, were recorded. If the patient had diabetes, information was collected on diabetes duration and treatment.

Data on the diagnosis of psychiatric illnesses were collected using the following classification: schizophrenia, schizoaffective disorder, bipolar affective disorder, depression, other psychosis, substance abuse, eating disorders, and other diagnoses. Duration of illness and treatment data were documented. Patients with two or more psychiatric diagnoses were noted. Psychotropic medications were categorized as anti-depressants, mood stabilizers, typical or atypical anti-psychotics, and both. Antipsychotic medication type was recorded.

Biochemical laboratory values (HbA1c, haemoglobin, creatinine, estimated glomerular filtration rate, and fasting lipid profile) were extracted from medical records within three months of the admission date. The length of inpatient stay was recorded.

For patients who had multiple admissions, only the data from the initial admission was included in this study. This study was carried out in accordance with the recommendations of Austin Health Research Ethics Committee (LNR/15/Austin/41), who waived the need for informed consent for a planned practice change agreed to by the hospital senior medical staff members as part of the Austin Health Diabetes Discovery Initiative. The protocol was approved by the Austin Health Research Ethics Committee.

Patients were categorized into three glycemic categories according to the ADA guidelines using HbA1c definitions as follows: “No diabetes” defined as HbA1c less than or equal to 5.6% (38 mmol/mol), “Pre-diabetes” defined as HbA1c greater than or equal to 5.7% and less than or equal to 6.4% (39–46 mmol/mol), and “Diabetes” defined as HbA1c greater than or equal to 6.5% (48 mmol/mol) (13).

A total of 335 psychiatry inpatients formed the study cohort. Fourteen percent of these patients (95% CI: 10–18%, n = 46) had diabetes, 19% (95% CI: 15–23%, n = 63) had pre-diabetes, and 67% (95% CI: 62–72%, n = 226) had no diabetes. Only two patients had new diagnosis of diabetes, and there were none with type 1 diabetes. The median HbA1c was 7.3% (IQR 6.2, 8.7) or 56 mmol/mol (IQR 44, 72) in the diabetes group, 5.8% (IQR 5.7–5.9) or 40 mmol/mol (IQR 39–41) in the pre-diabetes group, and 5.4% (IQR 5.2–5.5) or 36 mmol/mol (IQR 33–37) in the no diabetes group (Table 1).

First, this study demonstrated high prevalence of pre-diabetes and diabetes in the inpatient psychiatry population, compared to age-matched rates of prevalence of diabetes in the general community. Second, diabetes was associated with a more prolonged psychiatric inpatient LOS. Third, increasing age and substance abuse were associated with higher rates of diabetes in the inpatient psychiatry population, independent of other risk factors. Fourth, diabetes was associated with lower employment rates. Fifth, in one-third of inpatients, weight and lipid profile was not recorded.

The rates of pre-diabetes and diabetes in this study were 19% and 14% respectively. Prior studies have similarly reported high rates of diabetes in those patients with psychosis living in the community (6). In the current study, we demonstrate a snapshot of the glycemic status of the inpatient psychiatry population who are likely a more vulnerable group, with regards to higher psychiatric illness severity, chronic illness and disability.

In the current study, a longer duration of psychiatric illness was not associated with diabetes presence. A study of two epidemiological databases of psychiatric inpatients over two different time periods did not find any association between diabetes and serious mental illness but reported an association between diabetes and psychotropic treatment (15). The lack of association may be due to the small population size, the variety of mental health diagnosis, the short follow-up, and not accounting for confounding factors (15).

There was a significant gender bias skewed toward males, representing approximately 70% of psychiatric inpatients. This finding is in line with previous studies demonstrating that males present with psychiatric disorders requiring admission (16).

The most prevalent psychiatry diagnosis in our patient cohort included schizophrenia, depression, and substance abuse, which are reflective of the disease burden in the acute inpatient psychiatry patient. Substance abuse has been described in previous studies to be associated with the development of diabetes through multiple mechanisms, including hyperglycemia, hyperinsulinemia, poor overall physical health, higher rates of psychological distress, poor compliance to psychotropic therapy, and increasing rate of mental health admissions (6, 7, 17). It is, therefore, challenging to pinpoint one factor alone in the development of diabetes.

Many studies have shown that use of atypical psychotropic therapy has been associated with weight gain, impaired glucose metabolism, and increased risk of metabolic syndrome (18). Contrary to previous studies, we did not find a significant association between the type of psychotropic therapy patients received and prevalence of diabetes except in those inpatients who were taking aripiprazole. In fact aripiprazole has been shown in two studies to relate to a favorable metabolic profile (19, 20). Perhaps our data highlighted those individuals who were in the process of being transitioned to aripiprazole from a different psychotropic agent and hence this association may reflect the severity of underlying psychiatric disease and longer prior duration of antipsychotic use.

Limitations of the current study include lack of long-term medication exposures, including drug dosage prior to admission. Lifestyle factors, such as smoking, alcohol consumption, and substance abuse, may be underreported or inaccurately recorded. Clinical variables, such as weight and lipid profile, were missing in a significant proportion of the inpatients, perhaps reflecting the difficulty of obtaining a thorough physical examination and full metabolic profile in vulnerable psychiatry inpatients as has been described in previous studies (21, 22). Due to the limited data on the clinical characteristics, we were not able to make a comment on the presence of the metabolic syndrome in the current cohort. We were, therefore, not able to incorporate HbA1c into the revised definition of metabolic syndrome to enhance the detection of hyperglycemia (23). Additionally, ethnicity data was not routinely recorded.

Multivariable analysis highlighted variables associated with the presence of diabetes which may be useful in early flagging of those patients at highest risk of developing diabetes, namely, age, substance abuse, and presence of cardiovascular risk factors. Multivariable analysis also highlighted that patients with diabetes were more likely to have a longer length of inpatient psychiatry stay, suggesting perhaps that mental illness is more severe in people with diabetes.

However, given that this is an observational study, it is difficult to ascertain cause and effect. For example, the use of aripiprazole could reflect severity of mental illness and may be a confounder.

Current recommendations from Diabetes Australia are that individuals should be screened every 3 years from the age of 40 (24). The only relevant reference to screening those with mental illness is that the guideline suggests screening inpatients on antipsychotic medication alone, not including other psychiatric medications. A consensus statement developed by the ADA in 2004 discusses the screening for hyperglycemia in people treated specifically with antipsychotic medications (13). However, this may not capture other patients with mental illness who are on other psychiatric medications and may be at risk of developing diabetes. The New South Wales Health Clinical algorithm “Don’t Just Screen, Intervene” (25) recommends measurement of fasting glucose or HbA1c every 3–6 months in people receiving antipsychotic medications, for early detection and intervention. The National Institute for Health and Care Excellence Guidelines recommend diabetes screening prior to commencement of antipsychotic medication, 3 months later, then annually (26). Over one-third of our patient group did not have a weight or lipid profile recorded at baseline. This is a significant proportion of patients who are not getting optimal screening and, therefore, not being provided with the opportunity for optimization of management. Our current hospital guidelines suggest screening for diabetes as well other metabolic parameters in any patient prescribed psychotropic medications regardless of age (27). However, the challenge is obviously in implementing these guidelines as well ongoing management of these patients due to their potential lack of insight and care secondary to their mental illness. Barriers to screening, diagnosis, and monitoring of physical conditions in patients with mental illness are manifold and have already been described in many studies (28–31). Nevertheless, a hospital admission is an opportunity to screen for and initiate treatment of diabetes in all people with severe mental illness. Furthermore, it is an ideal opportunity to optimize therapy in a setting where admissions are often protracted and education in diabetes self-care and diet can be initiated once the patients is sufficiently well.

Metformin coupled with a lifestyle intervention program has been proposed in people at high risk of diabetes for cardio-metabolic protection as it has been shown to improve weight and metabolic parameters in normo-glycemic patients with psychosis commencing or receiving antipsychotic medication (32–34). Novel diabetic agents such as GLP-1 agonist are also being studied for management of diabetes and obesity in psychiatry populations on antipsychotic medications (35).

The prevalence of type 2 diabetes and pre-diabetes in our inpatient psychiatry population was high compared to age-matched rates of prevalence of diabetes in the general community and reflected the poor physical health of patients with mental illness. There was a strong association between increased age, lower employment rates, and substance abuse with the prevalence of diabetes, independent of other risk factors, as well prolonged inpatient LOS. While there are good guidelines for diagnosis and managing diabetes in these patients, one-third of our patients did not have appropriate cardio-metabolic screening as per our current guidelines. The challenges lie in health professionals implementing these guidelines due to a number of factors, including well-defined disparities in the delivery of health care to people with severe mental illness and bidirectional lack of engagement. The management of glycemic status in psychiatric inpatients following discharge may also be challenging and hence routine HbA1c testing as an inpatient presents an opportunity to address and improve glycemic management during the inpatient stay.

PN and EIE initiated the study, participated in its design, conception, and co-ordination, helped in the collection of data for analysis and interpretation, drafting and editing of the article, and final approval for publication. LC contributed to the conception and design of the study, performed the statistical analysis, drafting and editing of the article, and final approval for publication. AK, HW, AM, AY, EC, and QL contributed to the design of the study, collection of data for analysis and interpretation, editing of the article, and final approval for publication. RK contributed to design of the study, analysis of data and drafting and editing of the article, and final approval for publication. MH contributed to the analysis of the data, interpretation of the data, editing of the article, and final approval for publication. GH, EO-J, RR, and KS contributed to the design of the study, analysis of data and editing of the article, and final approval for publication. JZ contributed to the design of the study, analysis of data, and editing of the article. All authors have read and approved the final version of the manuscript and final approval for publication. PN, LC, and EIE are the guarantors of this work and, as such, had full access to all the data in the study and take full responsibility for the integrity of the data and the accuracy of the data analysis and final approval for publication.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a shared affiliation, though no other collaboration, with one of the authors (KS) and states that the process nevertheless met the standards of a fair and objective review.