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 RESEARCH ARTICLE

Diabetes prevalence estimates in schizophrenia and risk factor assessment

Tami Argo, PharmD, MS, BCPP

Iowa City Veterans Affairs Medical Center, Iowa City, IA, USA

Ryan Carnahan, PharmD, MS, BCPP

University of Iowa College of Public Health, Iowa City, IA, USA

Mitchell Barnett, PharmD, MS

Touro University-California, Vallejo, CA, USA

Timothy L. Holman, MA

University of Iowa College of Medicine, Iowa City, IA, USA

Paul J. Perry, PhD, BCPP, FCCP

Touro University-California College of Pharmacy, Vallejo, CA, USA, University of Iowa, Iowa City, IA, USA

BACKGROUND: Atypical antipsychotics have been indirectly associated with the diagnosis of type 2 diabetes mellitus (T2DM) in patients with schizophrenia. The purpose of this cross-sectional study was to determine the prevalence of T2DM and to examine the risk factors associated with T2DM among outpatients diagnosed with schizophrenia. The study also sought to determine which risk factors are of particular screening importance in monitoring the metabolic status of these patients.

METHODS: This study included 202 patients diagnosed with schizophrenia. Data on a number of known and hypothesized risk factors for T2DM were collected.

RESULTS: Risk factors for T2DM identified by bivariate analyses in this sample included older age, waist-to-hip ratio >1.0, sedentary lifestyle, number of hours worked per week, hyperlipidemia, previous screening for T2DM, higher random blood glucose, and number of years on atypical antipsychotics risperidone or olanzapine. However, further scrutiny using multiple logistic regression identified only sedentary lifestyle, waist-to-hip ratio ≥1.0, and a diagnosis of hyperlipidemia as significant risk factors in these patients. Similar to other studies, there was an 11.5% (22/192) lifetime prevalence rate of diabetes among this population.

CONCLUSIONS: Risk factors traditionally associated with T2DM, as well as waist-to-hip ratio, are the factors most strongly associated with increased risk of diabetes in patients with schizophrenia.

KEYWORDS: antipsychotic, diabetes, schizophrenia, prevalence, risk factors

ANNALS OF CLINICAL PSYCHIATRY 2011;23(2):117–124

  INTRODUCTION

Currently, type 2 diabetes mellitus (T2DM) is approaching epidemic proportion in the United States. Over the past 2 decades, rates of obesity have increased 3-fold with a lock-step increase in the rates of T2DM.1 The National Health Interview Survey reported the prevalence rates of T2DM in 1994 to be 1.2% among persons age 18 to 44, and 6.3% among persons age 45 to 64.2 By 2006, these rates had doubled to 2.7% and 10.6%, respectively.3 Of even greater public health concern is the estimate that a large proportion of patients with T2DM in the United States are undiagnosed.4 Based on an overall estimated 9.3% prevalence rate of T2DM in adults age ≥18, nearly 1 of every 3 diabetics (2.8%) remains unidentified and untreated for T2DM.5

In addition to the growing public health concerns of T2DM, the need for screening for metabolic conditions such as T2DM among patients with serious mental illnesses has become apparent and acknowledged. In population samples managed before the advent of atypical antipsychotic (AAP) agents, individuals diagnosed with schizophrenia were shown to have a higher risk of developing T2DM than the general population.6-8 A national survey of individuals diagnosed with schizophrenia found a lifetime prevalence rate of 14.9% and a current prevalence rate of 10.8%.9 The average age of this population was 43. The Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study reported the only other published prevalence rate of diabetes in a population of patients with schizophrenia, which was 13%.10 Additionally, the rate of T2DM in first-degree family members of patients with schizophrenia is reported to be between 18% to 30%, which is much higher than the rate estimated to be found in general population samples (1% to 6%).11

Confirmation of these prevalence rates of illness in other samples of patients with schizophrenia is warranted, to better gauge the burden of T2DM in this population. Lack of engagement in health-promoting behaviors and poor nutritional habits may play a role in the development of T2DM in patients with schizophrenia.12,13 However, it is unlikely that behavioral factors alone are responsible for the increased risk of T2DM in this population. Retrospective epidemiologic study14-20 and postmarketing surveillance21-24 of AAP agents have implicated their use with the development of T2DM in patients with schizophrenia. In addition, it is the exception rather than the norm for T2DM to present as an isolated medical problem in patients with schizophrenia. Other metabolic effects that can occur with AAP treatment include weight gain,25 metabolic syndrome,26-29 and hyperlipidemia,30-34 as well as secondary sequelae of hypertension and heart disease.35-37

Since the indirect association between AAP agents and metabolic disturbances such as weight gain, T2DM, and hyperlipidemia became obvious, expert consensus panels have developed clinical monitoring guidelines for patients receiving antipsychotic therapy.38 There are currently 6 sets of antipsychotic monitoring guidelines available, which have been reviewed by Cohn and Sernyak.39 The frequency at which screening and monitoring of T2DM should occur in this population is guided by clinical expert opinion rather than by research evidence. While the presence of primary risk factors for T2DM may predict development of this disease in patients with schizophrenia, the literature is scarce. Patients with schizophrenia may have other exposures (such as AAP use) that may independently predict or modify effects of known risk factors for T2DM. Ultimately, more specific and cost-effective T2DM screening recommendations for people with schizophrenia will be warranted. This study aimed to calculate the current prevalence rate of T2DM in an outpatient population with schizophrenia, and assess the presence of known and possible risk factors for T2DM that may have utility in monitoring the metabolic status of these patients.

  METHODS

Design

This investigation employed a cross-sectional design utilizing a convenience sample. This design was chosen for ease in computing a prevalence estimate of T2DM, our primary objective. The University of Iowa’s Institutional Review Board supervised the project to ensure the safety of the participants involved. Informed consent was obtained from all participants prior to data collection.

Sample

Eligible participants included men and women age ≥18 with a current diagnosis of schizophrenia at the Outpatient Adult Psychiatry Clinic at University of Iowa Health Care. Patients reporting only typical antipsychotic use were originally invited to participate in the study. However, because of the relative few number of such users (n=10), along with concerns that patients taking typical antipsychotics may represent a different schizophrenia cohort, these individuals were subsequently excluded from the study. AAP users electing to be enrolled (n=192) were screened for diabetes by 1 of 2 methods: 1) participants with a medical record documenting T2DM were considered to be diabetic; and 2) participants without a history of diabetes were asked to undergo a random capillary blood glucose test. Those with a random screening blood glucose >120 mg/dL (6.6 mmol/L) were asked to undergo a fasting serum glucose measurement. This cutoff value has demonstrated a sensitivity and specificity of 84% and 88%, respectively, in a community sample.40 This procedure also follows the recommendations for epidemiologic studies from the World Health Organization’s report on the definition, diagnosis, and classification of T2DM and its complications.41 Participants with a fasting serum glucose >126 mg/dL (6.93 mmol/L) were diagnosed with T2DM. Primary and psychiatric care providers were informed of the test results so that appropriate management strategies could be implemented, and/or to aid in diagnosing the presence or absence of T2DM. Participants with a current diagnosis of hypertension, who were on antihypertensive therapy, or who had a blood pressure >140/90 mm Hg at the screening visit were categorized as hypertensive. Those with a current diagnosis of hyperlipidemia, and/or who were receiving HMG-CoA reductase inhibitor (statin) therapy were considered to have hyperlipidemia.

Risk factor assessment

Data on a number of demographic and clinical variables were collected, including age, sex, race, insurance status (public or private), a visit to a psychiatric provider in the last month, a visit to a nonpsychiatric medical practitioner in the last 6 months, smoking status (pack-years), current alcohol use (yes or no), immediate family history of T2DM (parents and siblings), body mass index (BMI), waist-to-hip circumference ratio, activity level (sedentary or nonsedentary), number of hours worked per day, hypertension, and hyperlipidemia. Previous long-acting injectable use with haloperidol, fluphenazine, or risperidone (yes or no) was elicited as a proxy for oral antipsychotic nonadherence. Additionally, number of years taking AAP agents was collected, and duration of treatment was calculated for individual agents.

Statistical analysis

Comparisons between diabetic and nondiabetic patients were made using χ2 tests for categorical variables and t tests for continuous variables. A multiple logistic regression analysis was conducted to examine potential t test risk factors for the presence of T2DM. Covariates examined in the multiple logistic regression model included: age, sex, race, marital status, type of insurance, smoking history (pack years), current alcohol use (yes or no), hours worked per week, sedentary lifestyle, the presence of a first-degree relative with diabetes, waist-to-hip circumference ratio >1.0, presence of recent scheduled nonpsychiatric and psychiatric visits, hypertension, hyperlipidemia, and years of exposure to individual AAP agents (aripiprazole, clozapine, olanzapine, quetiapine, ziprasidone). Years of exposure to each AAP were kept in the model regardless of significance using a backward manual selection method, as the goal was to examine any association of exposure to individual AAP agents with diabetes. Comparisons among all possible AAP pairings were generated using a contrast statement at the end of the model statement. Due to concerns of colinearity in the model, the variation inflation factor (VIF) for each predictor in the multivariate model was calculated. None of the VIFs were >1.29, suggesting that colinearity was not a significant problem in the model.

All analyses were conducted using Statistical Analysis System (SAS) for Windows, Version 9.1 (SAS Institute; Cary, NC).

  RESULTS

Characteristics of the final 192 participants enrolled in the study are listed in TABLE 1. The lifetime prevalence rate was 11.5% (22/192) while the current prevalence rate was 10.9% (21/192). The mean age was 38. Demographically 70% of patients were male, 88% were white, 42% were married, and 82% had public insurance. The majority (66%) of participants were not currently working. The mean BMI was 29.9 kg/m2, and 25% of the study patients had a waist-to-hip ratio >1.0. A sedentary lifestyle was reported by 60% of participants. Over one-third (36%) had received depot antipsychotic injections. Diagnoses of hypertension and hyperlipidemia were ascertained in 23% and 26% of the participants, respectively. The average length of time on AAP therapy was >4 years. More specifically, participants had received olanzapine for the longest (mean 4 years) period of time, and aripiprazole and ziprasidone for the shortest periods of time (means of <1 year each among those who had received the agents). Less than half of the patients (79/192) reported prior screening for T2DM, with 9% (18/192) diagnosed with T2DM prior to the study. Screening identified 4 additional individuals with T2DM, for a total of 12% (22/192) of the total study sample. The mean random capillary blood glucose level was 113 mg/dL (6.3 mmol/L). It should be noted that random glucose measurements was not performed on those 18 participants already diagnosed with T2DM prior to the visit.

Significant risk factors for T2DM identified by the bivariate analyses included, being older; having a waist-to-hip ratio >1.0, a sedentary lifestyle, number of hours worked per week, hyperlipidemia, previous screening for T2DM, higher random blood glucose level, number of years on AAPs (P < .05), and years of exposure to olanzapine and risperidone (P < .05). Conversely, the following were not associated with T2DM: sex, race (white vs non-white), being married, having public insurance, smoking history, alcohol use, a first-degree relative with T2DM, BMI, previous decanoate antipsychotic use, recently scheduled nonpsychiatric and psychiatric visits, and a diagnosis of hypertension (TABLE 2).

A multiple logistic regression analysis examining variables in TABLE 2 as predictors for T2DM was performed. The only significant predictors identified were sedentary lifestyle (odds ratio [OR] 3.70; 95% confidence interval [CI], 1.05 to 13.06; P=.04), waist-to-hip ratio ≥1.0 (OR 3.22; 95% CI, 1.13 to 9.17; P < .01) and having hyperlipidemia (OR 4.97; 95% CI, 1.66 to 14.85; P < .01) (TABLE 3). Overall fit of the model, as measured by the C statistic, was .81, indicating excellent discrimination. No significant differences in odds of diabetes were noted among the individual AAP agents, using years of total exposure to each agent (TABLE 3).


TABLE 1

Patient characteristics (n=192)

  Mean (SD)
Mean age (years) 38.0 (10.8)
BMI 29.9 (8.4)
Smoking pack (years) 14.7 (19.1)
Number of years on an atypical antipsychotic 4.6 (3.9)
Number of years on an individual atypical antipsychotica  
  Aripiprazole (n=70) 0.6 (0.6)
  Clozapine (n=50) 3.5 (4.1)
  Olanzapine (n=120) 2.2 (2.4)
  Quetiapine (n=78) 1.7 (2.0)
  Risperidone (n=138) 1.6 (2.3)
  Ziprasidone (n=62) 0.8 (1.0)
Mean random glucose (mg/dL) 112.7 (34.7)
  No. (%)
Male 135 (70.3%)
White 169 (88%)
Married 81 (42.2%)
Public insurance 157 (81.8%)
Waist-to-hip ratio >1.0 48 (25%)
Current alcohol use 82 (42.7%)
First-degree relative with T2DM 55 (28.7%)
Sedentary lifestyle 116 (60.4%)
Hours worked per week  
  None 126 (65.6%)
  >0 to 10 hours 18 (9.4%)
  >10 to 20 hours 30 (15.6%)
  >20 hours 18 (9.4%)
Previous decanoate antipsychotic injection use 69 (35.9%)
Scheduled nonpsychiatric visit in previous 6 months 107 (55.7%)
Scheduled psychiatric visit in previous month 141 (73.4%)
Hypertension 45 (23.4%)
Hyperlipidemia 50 (26%)
Screened previously for T2DM 79 (42%)
Current diagnosis of T2DM 18 (9.4%)
Random glucose >120 mg/dL 50 (26%)
  Fasting blood glucose >126 mg/dL (out of 50 participants) 4 (2.1%)
New or current diagnosis of T2DM 22 (11.5%)
aMean (SD) for individual antipsychotics describes only those patients who had received the antipsychotics.
BMI: body mass index; SD: standard deviation; T2DM: type 2 diabetes mellitus.

TABLE 2

Characteristics of participants with and without diabetes

Mean (SD) Diabetes (n=22) No diabetes (n=170) P value
Mean age (years) 43.3 (9.9) 37.3 (10.8) .02
BMI 33.1 (8.0) 29.5 (8.3) .05
Smoking pack (years) 16.4 (21.2) 14.5 (18.8) .67
Mean random glucosea (mg/dL) 161.8 (76.1) 108.0 (23.1) .01
Number of years on atypical antipsychotics 6.8 (5.2) 4.3 (3.7) <.01
Number of years on individual atypical antipsychoticsb      
  Aripiprazole (n=70) 0.8 (0.6) 0.6 (0.7) .38
  Clozapine (n=50) 3.0 (3.2) 3.7 (4.4) .68
  Olanzapine (n=120) 4.0 (4.2) 2.0 (2.0) <.01
  Quetiapine (n=78) 1.4 (1.3) 1.7 (2.1) .65
  Risperidone (n=138) 2.5 (3.3) 1.4 (2.1) .08
  Ziprasidone (n=62) 0.5 (0.5) 0.9 (1.0) .25
No. (%)      
Waist-to-hip ratio >1.0 12 (54.5%) 36 (21.2%) <.01
Ever smoked 14 (63.6%) 129 (75.9%) .22
Current alcohol use 8 (36.4%) 74 (43.5%) .53
First-degree relative with T2DM 8 (36.7%) 47 (27.6%) .40
Sedentary lifestyle 18 (81.8%) 98 (57.6%) .03
Hours worked per week     .04
None 14 (63.6%) 112 (65.8%)  
  >0 to 10 hours 6 (27.3%) 12 (7.1%)  
  >10 to 20 hours 1 (4.6%) 29 (17.1%)  
  >20 hours 1 (4.6%) 17 (10%)  
Previous decanoate antipsychotic injection use 7 (31.8%) 62 (36.5%) .67
Scheduled nonpsychiatric visit in previous 6 months 16 (72.7%) 91 (53.5%) .08
Scheduled psychiatric visit in previous month 14 (63.6%) 127 (74.7%) .27
Hypertension 8 (34.8%) 37 (21.8%) .13
Hyperlipidemia 12 (54.5%) 38 (22.4%) .01
Screened previously for T2DM 21 (95.5%) 58 (34.9%) <.01
aDoes not include participants already diagnosed with T2DM prior to study.
bMean±SD presented for only those participants who received the individual atypical antipsychotic. BMI: body mass index; T2DM: type 2 diabetes mellitus.

TABLE 3

Multiple logistic regression model assessing the risk of diabetes associated with exposure to individual atypical antipsychotic agentsa

  Odds ratio 95% Confidence interval P value
Sedentary lifestyle 3.70 1.05 to 13.06 .04
Waist-to-hip ratio >1.0 3.22 1.13 to 9.17 <.01
Hyperlipidemia 4.97 1.66 to 14.85 <.01
Olanzapine      
  Olanzapine vs risperidone 1.12 0.86 to 1.45 .41
  Olanzapine vs ziprasidone 1.38 0.47 to 4.03 .55
  Olanzapine vs clozapine 1.17 0.94 to 1.46 .16
  Olanzapine vs aripiprazole 0.97 0.32 to 2.98 .97
  Olanzapine vs quetiapine 1.36 0.87 to 2.16 .19
Risperidone      
  Risperidone vs ziprasidone 1.24 0.42 to 3.66 .70
  Risperidone vs clozapine 1.05 0.84 to 1.32 .68
  Risperidone vs aripiprazole 0.87 0.27 to 2.77 .82
  Risperidone vs quetiapine 1.22 0.79 to 1.89 .37
Ziprasidone      
  Ziprasidone vs clozapine 0.85 0.29 to 2.44 .76
  Ziprasidone vs aripiprazole 0.70 0.12 to 4.21 .70
  Ziprasidone vs quetiapine 0.98 0.30 to 3.23 .98
Clozapine      
  Clozapine vs aripiprazole 0.83 0.27 to 2.58 .75
  Clozapine vs quetiapine 1.17 0.77 to 1.77 .47
Aripiprazole      
  Aripiprazole vs quetiapine 1.40 0.43 to 4.56 .57
aControlled for possibility of age, sex, race, marital status, insurance type, waist-to-hip ratio >1.0, pack-year smoking history, current alcohol use, presence of first-degree relative with type 2 diabetes mellitus, sedentary lifestyle, hours worked per week, previous decanoate use, scheduled nonpsychiatric and psychiatric visits, hypertension, and hyperlipidemia.

  DISCUSSION

Initial evidence from samples of patients treated in the early 1990s, before the advent of AAP agents, suggests that people with schizophrenia are more likely to develop T2DM than those in the general population.9 Our cross-sectional study found an 11.5% lifetime prevalence of diabetes among people with schizophrenia. This mirrors earlier reports, including the 13% prevalence of diabetes found in the CATIE study.10 This provides further evidence that the risk of diabetes in patients diagnosed with schizophrenia is elevated compared with that of the general population.

Current literature does not provide a clear understanding of which risk factors best predict the development of T2DM in patients with schizophrenia. It is likely that the presence of primary risk factors is more important than exposure to AAP agents in the development of T2DM in patients with schizophrenia. One study evaluated risk factors for T2DM in patients with schizophrenia and found them to be similar to those in the general population.9 These risk factors included female sex, non-white race, increasing age, never married, and lower educational attainment. Other possible risk factors for T2DM, including length of exposure to AAP treatment, were not evaluated in this previous study. However, it should be mentioned that some AAPs may contribute to weight gain and thus indirectly contribute to other possible risk factors for T2DM, such as waist circumference. Effects of AAP treatment on intra-abdominal fat, perhaps a proxy indicator of waist circumference, have been shown to be inconsistent in current available literature. Further clouding the picture is a body of evidence showing the presence of increased intra-abdominal and visceral fat in the absence of weight gain or AAP treatment in patients with schizophrenia, indicating that the presence of schizophrenia itself may be associated with increased intra-abdominal fat stores.42,43

The most recent position statement from the American Diabetes Association (ADA) regarding diabetes screening delineates major risk factors for T2DM.44 These include family history of a first-degree relative with T2DM, being overweight, habitual physical inactivity, particular races/ethnicities (eg, African Americans, Hispanic Americans, Native Americans, Asian Americans, and Pacific Islanders), previously identified impaired fasting glucose or glucose tolerance, hypertension (>140/90 mm Hg or taking medication for hypertension), high-density lipoprotein cholesterol <35 mg/dL and/or triglyceride level >250 mg/dL, a history of gestational T2DM or delivery of a baby weighing >9 lbs, polycystic ovary syndrome, and other conditions (including acanthosis nigricans) that are associated with insulin resistance. The ADA also recommends that “high-risk” individuals be evaluated at 3-year intervals starting at age 45.

Assuming the ADA risk factors are representative of patients diagnosed with schizophrenia in general, the high prevalence of risk factors for diabetes is likely part of the explanation for the high prevalence of diabetes in our sample, regardless of the external variable of antipsychotic exposure. When examining potential risk factors for diabetes, findings from the bivariate analyses showed an association with ADA risk factors and presence of diabetes. These variables included being older, a sedentary lifestyle, hyperlipidemia, and prior screening for T2DM. Other variables significantly associated with diabetes from bivariate analyses included having a waist-to-hip ratio >1.0 and number of years on AAPs (TABLE 2). Multiple logistic regression analysis identified only sedentary lifestyle, waist-to-hip ratio ≥1.0, and a diagnosis of hyperlipidemia as significant risk factors in this patient sample (TABLE 3).

Our analyses had a number of limitations. First, given that the majority of nondiabetic participants reported not being screened for diabetes, it is likely that many had never been screened for hyperlipidemia either. Those with T2DM were more likely to have been screened for hyperlipidemia than those without T2DM. It also may be argued that hyperlipidemia should not be considered a causative risk factor for diabetes because the 2 disorders are related but one does not cause the other, per se. Further, presence of hyperlipidemia and hypertension, as well as other important risk factors, such as family history, could have been influenced by recall bias as they were in part dependent on patient self-report. With regard to other risk factors, the number of patients with a history of gestational diabetes (n=3) was very low, causing the OR estimate for this risk factor to be unreliable. Thus, one may argue that the analysis was underpowered to detect certain risk factors relevant to predicting diabetes. In addition, comparisons conducted in the bivariate analysis may be susceptible to type I errors, as no adjustments were made for multiple comparisons.

It should be noted that the cross-sectional nature of this study, and the fact that most participants had already been diagnosed with diabetes, limits the ability to establish a temporal relationship of that exposure to the development of diabetes. In addition, there is a possibility for bias in examining drug exposure because a drug may have been administered after diabetes was diagnosed, such as in the likely case of aripiprazole and ziprasidone. Also, the race of the study sample was primarily white, and may not be representative of non-white ethnic groups. Lastly, the sample size that we enrolled was smaller than our estimated sample size, which may have limited our ability to detect other statistically significant risk factors associated with diabetes.

As waist-to-hip ratio >1.0 and BMI were significantly correlated, only the variable for waist-to-hip ratio >1.0 was entered into the final multivariate backward selection model. In addition, several of the ADA risk factors as variables may have “fallen out” of significance in the regression model due to significant correlations with other ADA risk factor variables. In particular, hyperlipidemia was significantly correlated with age and hypertension, while sedentary life-style was significantly related to a positive family history of diabetes. Keeping these limitations in mind, we felt that the non-drug risk factors identified were consistent with risk factors reported by the ADA.44 When considering the duration of exposure to AAPs, only bivariate analysis of total years exposure and years of exposure to olanzapine and risperidone were found to be significantly associated with diabetes. The ability to identify combined years on AAPs as a predictive factor likely is an artifact of the relative long-term use of AAPs in the sample (>4.5 years on average). Findings from previous studies report that drug dosage increases are not uncommon if a patient remains on a particular agent. This, coupled with a linked association between dosage and weight gain for several of the agents, likely explains this finding.45

With regard to the efficiency of mass screening for diabetes, the majority of diabetic patients had been diagnosed with diabetes prior to this study. Screening identified only 4 new cases of diabetes, despite the fact that only 42% of the sample reported having been screened for diabetes prior to this study. One of every 6 diabetics was undiagnosed in our sample. This low rate of identification of new cases of diabetes does not argue against the utility of generalized screening in this patient population. Blood glucose measurements are inexpensive, and diabetes can develop during antipsychotic treatment outside of the context of weight gain or obesity.46,47

  CONCLUSIONS

This study confirmed the high current and lifetime prevalence of diabetes among patients diagnosed with schizophrenia, supporting the need for enhanced monitoring for diabetes in this population. It also helped to confirm a high prevalence of ADA risk factors in people with schizophrenia. Risk factors for diabetes in this sample identified by the bivariate analyses included older age, waist-to-hip ratio >1.0, a sedentary lifestyle, number of hours worked per week, hyperlipidemia, previous screening for T2DM, higher random blood glucose level, and number of years on the AAPs risperidone or olanzapine. When these relationships were modeled to control for other confounding factors, only sedentary lifestyle, hyperlipidemia, and waist-to-hip ratio >1.0 remained significantly associated with development of T2DM in our population of patients with schizophrenia. Though it is difficult to establish causation due to the cross-sectional nature of the study, these risk factors are consistent with current knowledge about diabetes risk factors and metabolic effects of AAPs.

It is likely that the presence of primary risk factors is more important in the development of T2DM in patients with schizophrenia than exposure to AAPs. Whatever the mechanism by which the increased risk of diabetes occurs, people with schizophrenia have been shown to be more likely to develop T2DM than those in the general population. The development of appropriate screening guidelines will help clinicians decide which patients are at greatest risk of developing T2DM and ensure that the frequency of T2DM screening is adequate to reduce associated morbidity and mortality. These screening guidelines should include assessment of level of activity and waist-to-hip ratio, both of which appear to be strongly associated with increased risk of diabetes in patients with schizophrenia.

ACKNOWLEDGEMENTS: Supported by an investigator-initiated grant through Eli Lilly and Company, Indianapolis, IN.

DISCLOSURES: Dr. Carnahan has received research support from Forest Laboratories, Boehringer Ingelheim, and Wyeth. Drs. Argo, Barnett, Holman, and Perry report no financial relationships within the last 5 years with any company whose products are mentioned in this article or with manufacturers of competing products. The authors alone are responsible for the content and writing of the paper.

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CORRESPONDENCE: Paul J. Perry, PhD, BCPP, FCCP, Touro University-California College of Pharmacy, 1310 Johnson Lane, Mare Island, Vallejo, CA 94592 USA E-MAIL: paul.perry@tu.edu