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. 2026 Oct 9;19:650265. doi: 10.2147/DMSO.S650265

Diabetes Mellitus in Patients with Schizophrenia: A Systematic Review and Meta-Analysis of Prevalence of Types and Risk Factors

Kimia Kake 1,2, Milad Jalilian 1,2,✉
PMCID: PMC13660731  PMID: 42872196

Abstract

Background

Schizophrenia is associated with an increased risk of diabetes mellitus (DM) and type 2 diabetes mellitus (T2DM), yet the overall burden and related risk factors remain incompletely characterized.

Aim

This study aimed to estimate the prevalence of DM in overall and T2DM in patients with schizophrenia and to summarize associated risk factors.

Methods

This PRISMA-guided systematic review and meta-analysis included observational studies reporting DM or T2DM in patients with schizophrenia. Databases were systematically searched. Pooled prevalence estimates were calculated using a random-effects model in CMA software. Heterogeneity was assessed using Cochran’s Q test and I2, while publication bias was evaluated using Egger’s regression test and trim-and-fill analysis.

Results

Thirty-five studies involving 139,304 individuals were included, and 34 studies contributed to the meta-analysis. The pooled prevalence of DM was 10.4% (95% CI: 8.3–12.9%), and the pooled prevalence of T2DM was 13.2% (95% CI: 9.1–18.9%). Between-study heterogeneity was substantial for both outcomes (I2 = 99.49% and 99.38%, respectively). Egger’s test suggested possible publication bias; however, trim-and-fill analysis identified no missing studies and did not alter the pooled estimates. Commonly reported risk factors included older age, female sex, obesity or higher body mass index, family history of diabetes, sedentary lifestyle, lower socioeconomic status, longer illness duration, and antipsychotic exposure, particularly clozapine and olanzapine.

Conclusion

Overall diabetes, particularly type 2 diabetes, is prevalent among patients with schizophrenia and associated with demographic, clinical, treatment-related, and medication-related risk factors. These findings support routine metabolic screening and early preventive interventions to reduce diabetes risk and improve health outcomes in this high-risk population.

Keywords: schizophrenia, diabetes mellitus, type 2 diabetes mellitus, prevalence, risk factor

Introduction

Diabetes mellitus (DM) is one of the most common chronic diseases worldwide, imposing a substantial burden on individuals and healthcare systems. In Europe, approximately 9.8% of adults were estimated to have diabetes in 2024, and both its prevalence and associated burden are expected to continue increasing.1 In the United States, recent NHANES-based data showed a total diabetes prevalence of 15.8% in adults (11.3% diagnosed and 4.5% undiagnosed).2 In Asia, the burden is increasing rapidly; for example, pooled diabetes prevalence in South Asia rose from 11.29% in 2000–2004 to 22.30% in 2020–2024, reflecting the region’s escalating metabolic disease load.3 The clinical course of diabetes is frequently complicated by a wide range of debilitating complications, from microvascular pathologies such as diabetic foot ulcers and lower-extremity amputation to macrovascular events such as acute myocardial infarction (AMI), coronary artery disease (CAD), and chronic heart failure (CHF) and also renal failure.4–9 Although genetic predisposition and lifestyle factors are well-established contributors, specific vulnerable populations, particularly patients with severe mental or psychological illnesses like schizophrenia, bear a disproportionately higher risk.10,11

Schizophrenia is a severe, chronic mental disorder characterized by profound disturbances in thought processes, perception, emotions, and behaviour. It affects approximately 0.2%–0.4% of the population across Europe, the United States, and Asia.12,13 Patients with schizophrenia have a substantially increased risk of developing type 2 diabetes mellitus due to multiple factors, with its prevalence estimated to be two to three times higher than in the general population.14,15 Moreover, when diabetes occurs in these individuals, the clinical trajectory is often more aggressive, leading to significantly higher rates of cardiovascular mortality and severe end-organ damage.16 This heightened vulnerability arises from a complex, multifactorial interplay. Disease-intrinsic factors, such as physical inactivity, poor dietary habits, and social isolation converge with the profound metabolic adverse effects of antipsychotic medications, including substantial weight gain, drug-induced hyperlipidemia, and direct dysregulation of glucose homeostasis.17–19

The association between schizophrenia and diabetes appears to involve overlapping biological, behavioral, and treatment-related mechanisms. Individuals with schizophrenia may have an underlying metabolic vulnerability involving impaired insulin sensitivity, chronic low-grade inflammation, and shared genetic susceptibility, while sedentary behavior, unhealthy dietary patterns, and social disadvantage may further increase metabolic risk. In addition, antipsychotic medications, particularly some second-generation agents, may contribute to weight gain and metabolic disturbances, including impaired glucose regulation and increased diabetes risk. Previous evidence has also suggested shared genetic pathways between schizophrenia and type 2 diabetes and reported inflammatory abnormalities that may contribute to this comorbidity.11,17–19

Given the complex relationship between schizophrenia and diabetes, particularly type 2 diabetes mellitus (T2DM), this systematic review and meta-analysis aimed to provide an updated quantitative assessment of the prevalence of overall diabetes and T2DM among patients with schizophrenia and to synthesize the major demographic, clinical, lifestyle, and treatment-related risk factors associated with diabetes in this population.

Methods

Study Design and Protocol

This study was designed and conducted as a systematic review and meta-analysis in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines.20 The study aimed to comprehensively assess the overall prevalence of diabetes and type 2 diabetes mellitus (T2DM) among patients with schizophrenia and identify diabetes-related risk factors in this population. The review protocol was developed based on PRISMA recommendations to guide the literature search, eligibility assessment, study screening, data extraction, data screening, and analysis. The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) under registration number CRD420261465691. In addition, the study protocol was registered at Kurdistan University of Medical Sciences under registration code IR.MUK.REC.1405.097.

Search Strategy

A comprehensive search of electronic databases and the scientific literature was conducted from inception to May 25, 2026. The search strategy used a structured combination of MeSH terms and free-text terms related to schizophrenia, diabetes mellitus, DM, type 2 diabetes mellitus, T2DM, prevalence, and risk factors. To maximize sensitivity and ensure comprehensive retrieval, the search strategy was tailored to each database. In addition, the reference lists of identified articles were manually screened to identify additional eligible studies. All retrieved records were imported into reference management software, where duplicates were identified, screened, and removed.

Information Sources

The international databases and sources searched included PubMed/MEDLINE, Embase, Web of Science, Scopus, ScienceDirect, CENTRAL, Google Scholar, and ClinicalTrials.gov. The reference lists of the identified studies were also manually screened to identify additional eligible articles that may not have been retrieved through the electronic database searches. The review considered observational studies reporting diabetes mellitus or T2DM outcomes among individuals with schizophrenia. Eligible evidence included studies conducted in different countries and using cross-sectional, case-control, or cohort designs.

Inclusion and Exclusion Criteria

Studies were considered eligible if they reported sufficient data on the prevalence of diabetes mellitus, type 2 diabetes mellitus (T2DM), or both among patients with schizophrenia, or provided adequate information to extract data on associated risk factors. Observational studies were eligible for inclusion. In contrast, reviews, meta-analyses, letters, commentaries, case reports, duplicate publications, and studies lacking sufficient extractable information were excluded. When an individual study reported more than one outcome relevant to the review, all eligible outcome data were retained for the synthesis.

Study Selection Process

The selection of eligible studies was conducted in two stages. First, two authors independently screened the titles and abstracts of all retrieved articles using EndNote, removing duplicates and clearly irrelevant studies. Subsequently, the full texts of the remaining articles were independently assessed by both authors against the predefined eligibility criteria. Any disagreements were resolved through discussion and consensus. The study selection process is summarized in the PRISMA flow diagram (Figure 1).

Figure 1.

A flowchart of study identification and screening process via databases and other methods. The flowchart illustrates the process of identifying and screening new studies through databases and registers and other methods. On the left, identification starts with records from databases totaling 173, with none from registers. Records removed before screening include 43 duplicates, none marked by automation tools and none removed for other reasons. Screening shows 155 records screened, with 89 excluded. Reports sought for retrieval are 5, with 5 not retrieved. Reports assessed for eligibility are 66, with exclusions due to insufficient data (7), irrelevant study designs (10), unclear findings (7) and unverified data (7). New studies included in review are 35, with reports of new included studies also 35. On the right, identification from websites, organizations and citation searching totals 25, with none from websites or organizations. Reports sought for retrieval and not retrieved are zero. Reports assessed for eligibility are 25, with none excluded.

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PRISMA flowchart for study Selection20.

Data Items

Data from the studies included in the systematic review were independently extracted by two authors. The extracted information included author name, study location, publication year, study design, study population, control group (if applicable), reported prevalence of diabetes mellitus or type 2 diabetes mellitus or both estimates if reported, reported risk factors, and study quality assessment.

Quality Assessment

The methodological quality of the included studies was assessed using the Newcastle–Ottawa Scale (NOS).21 The NOS assessment covered three main domains: selection of study groups, comparability between groups, and ascertainment of exposure or outcomes. The assessment was independently conducted by both authors, and any disagreements were resolved through discussion and consensus. The resulting NOS scores were used to evaluate the methodological quality of the observational evidence included in the review.

Meta-Analysis and Synthesis

Quantitative data synthesis and meta-analysis were performed using Comprehensive Meta-Analysis (CMA) software. Statistical heterogeneity was assessed using Cochran’s Q test and the I2 statistic. Given the substantial heterogeneity (I2 > 99%), a random-effects model was used to account for variability in study designs, population characteristics, and settings. Pooled estimates of the overall prevalence of diabetes and T2DM were calculated with 95% confidence intervals.

Study Risk of Bias Assessment

Publication bias and small-study effects were assessed using Egger’s regression test and funnel plots. When funnel plot asymmetry suggested potentially missing studies, a trim-and-fill analysis was performed as a sensitivity analysis to determine whether the pooled estimates changed after adjustment. Given the substantial heterogeneity, these findings were interpreted cautiously.

Results

Search Results and Article Selection

A total of 198 records were identified through the initial search of electronic databases and the reference lists of relevant articles. All retrieved records were imported into EndNote software for further screening. After removing 43 duplicate records, 155 articles were assessed based on their titles, abstracts, and study methodologies. Of these, 89 studies were excluded due to non-observational study designs or outcomes unrelated to the prevalence of diabetes among patients with schizophrenia.

The full texts of the remaining 66 articles were reviewed in detail. Subsequently, 31 studies were excluded because of insufficient data, irrelevant study designs, unclear findings, or results that could not be adequately verified. Ultimately, 35 studies met the eligibility criteria and were included in the systematic review. Among these, 34 studies reported data on the overall prevalence of diabetes and/or specifically on the prevalence of type 2 diabetes mellitus (T2DM) and were therefore included in the quantitative synthesis and meta-analysis. Additionally, 25 studies provided sufficient information regarding risk factors associated with diabetes in patients with schizophrenia and were included in the descriptive analysis (Tables 1–3 and Figure 1).

Table 1.

Charactersitics of Included Studies

Study/Year Design Location Patients Control NOS
Mäkikyrö et al, 199822 CS Finland
(1982–1994)		 89 SCZs 10,630 Patients without Psychiatric Diagnosis 5
Dixon et al, 200023 Retrospective CC USA 719 6066 Medicaid population 5
Dickerson et al, 200224 CS USA 43 43 reference sample 5
Curkendall et al, 200415 Retrospective CC Canada 3022 12,088 Patients without Psychiatric Diagnosis 7
Enger et al, 200425 Retrospective cohort USA 1920 treated schizophrenia patients 9600 general population controls 6
Sokal et al, 200426 CC- Retrospective USA 100 SCZs 100 affective disorders patients 6
Feldman et al, 200427 Retrospective cohort USA Not restricted to schizophrenia; elderly antipsychotic users (>60 years), including schizophrenia and dementia populations General elderly population not receiving antipsychotics 8
Goff et al, 200528 CS USA 689 patients 33,994 subjects from NHANES III 8
Hung et al, 200529 CS Taiwan 246 patients with schizophrenia General population data from Taiwan (n=1534) 7
Lambert et al, 200530 CC USA 3663 schizophrenia patients with new-onset T2DM 14,523 matched schizophrenia controls without diabetes 8
Osborn et al, 200631 CS UK 74 patients with SMI (majority schizophrenia/schizoaffective) 148 patients without SMI 6
Cohen et al, 200632 CS The Netherlands 266 SCZs 50,620 General Population 7
De Hert et al, 200633 CS Belgium 415 2524 7
Barnett et al, 200634 Retrospective cohort USA 996 with schizophrenia diagnosis in the full cohort Proton pump inhibitor users as control group
Suvisaari et al, 200835 CS Finland Psychosis Subjects
The number of SCZs not reported separately		 Subjects without psychotic disorder 8
Chien et al, 200936 CC- Retrospective Taiwan 4417 patients 762,223 subjects from the general population 7
Verma et al, 200937 CC Singapore 160 drug-naive patients 200 age-, gender-, and ethnicity-matched healthy controls 8
Bresee et al, 201038 Retrospective cohort Canada 28,755 patients 2,281,636 non-schizophrenic controls 7
Okumura et al, 201039 Retrospective cohort Japan 3849 patients Compared to age-gender adjusted standardized general rates 7
Nielsen et al, 201040 Cohort study Denmark 7139 antipsychotic-naïve schizophrenia patients - 9
Bresee et al, 201141 CS Canada 399 patients 120,044 non-schizophrenic controls 7
Mai et al, 201142 Retrospective cohort Australia 17,045 MHCs
Not clear for schizophrenia numbers.		 294,180 matched non-MHCs 6
Nuevo et al, 201143 CS 52 countries (WHO World Health Survey) 2352 patients with lifetime diagnosis of schizophrenia/psychosis (1069 without current symptoms + 1283 with current symptoms) General population without these symptoms/diagnoses 7
Phutane et al, 201144 CS USA 56 patients (first-episode psychosis) 145 matched controls from NHANES 7
Subashini et al, 201145 CC India 131 patients 524 healthy controls 7
Zhang et al, 201146 CS China 206 SCZs 615 matched normal controls 6
Argo et al, 201147 CS USA 202 outpatients with schizophrenia - 9
Kirkpatrick et al, 201248 CC Spain 64 drug naive/minimal
antipsychotic exposure (<1 week), out-patients		 85 Healthy controls 7
Morden et al, 201249 Retrospective cohort (8-year trend) USA 65,362 patients 65,362 matched veterans patients without SMI 7
Schoepf et al, 201214 Retrospective CC UK 679 SCZs 88,778 hospital controls 7
Schoepf et al, 201316 Retrospective CC UK 1418 SCZs 14,180 Non-SCZ Patients 7
Foley et al, 201450 CS Australia 1155 patients with psychosis General population survey data (AusDiab) 7
Foley et al, 201551 CS Australia 857 schizophrenia patients within 1642 psychosis cases - 7
Ingimarsson et al, 201752 Retrospective cohort Iceland 583 (188 clozapine-treated SCZ; 395 never-on-clozapine SCZ) Icelandic population controls 8
Fang et al, 202453 Retrospective Cohort-CC Taiwan 4606 SCZs 4606 Non-SCZ Controls 9
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Abbreviations: CS, Cross-sectional; SCZs, Schizophrenic Patients; CC, Case-control; SMI, Severe Mental Illness; MHCs, Mental Health Clients; NHANES, National Health and Nutrition Examination Survey.

Table 2.

Prevalence of Diabetes Mellitus and T2DM (if Reported Separately) in Schizophrenia Patients

Study/Year DM Prevalence - N (%) T2DM Prevalence - N (%)
Mäkikyrö et al, 199822 SCZs: 0/89 (0%)
Controls: 78/10630 (0.7%)		 Nrs
Dixon et al, 200023 - SCZs: 107/719 (14.9%)
Controls: 673/6066 (11.1%)
Dickerson et al, 200224 SCZs: 6/43 (14%) Nrs
Curkendall et al, 200415 SCZs: 91.7/1000 (9.17%)
Controls: 50.5/1000 (5.05%)		 Nrs
Enger et al, 200425 SCZs: − 6.2%
Controls: 3.1%
306 new-onset diabetes cases during follow-up		 Nrs
Sokal et al, 200426 SCZs: 10/100 (10%)
Controls: 15/100 (15%)		 Nrs
Feldman et al, 200427 SCZs: in Overall new-onset diabetes 753/30,953 (2.4%);
conventional antipsychotics: 238/11,546 (2.1%); atypical antipsychotics: 515/19,407 (2.7%)		 Nrs
Goff et al, 200528 SCZs: - (13%) Nrs
Hung et al, 200529 SCZs: 24/246 (9.8%) Nrs
Osborn et al, 200631 SCZs: 7/74 (9.6%) in SMI group
Controls: 4 (2.7%)		 Nrs
Cohen et al, 200632 - SCZs: 24/266 (9%)
Controls: 4.9%
De Hert et al, 200633 SCZs: 26/415 (6.3%)
97 (23.4%) prediabetic abnormalities		 Nrs
Barnett et al, 200634 SCZs: 150/996 (~15%) SCZs: 12.9%
Suvisaari et al, 200835 - SCZs: 22.0%
Controls: 6.1%
Chien et al, 200936 SCZs: 349/4417 (7.90%)
Controls: (5.57%)		 Nrs
Verma et al, 200937 SCZs: 8/160 (5%)
Controls: 1 (0.5%)		 Nrs
Bresee et al, 201038 SCZs: 2952/28755 (10.3%)
Controls: 126,817 (5.6%)		 Nrs
Okumura et al, 201039 SCZs: 332/3849 (8.6%) Nrs
Nielsen et al, 201040 - SCZs: 307/7139 (4.3%)
annual incidence 0.65%
Bresee et al, 201141 SCZs: - (11.9%)
Controls: - (5.3%)		 Nrs
Mai et al, 201142 SCZs: 4227/17045 (~24.8%) Nrs
Nuevo et al, 201143 SCZs: - (~ 6.5%)
(With current symptoms: 7.71%
Without current symtpms: 5.11%)		 Nrs
Phutane et al, 201144 SCZs: 0/56 (0%)
Controls: 2/145 (1%)		 Nrs
Subashini et al, 201145 SCZs: 20/131 (15.3%)
Controls: 38/524 (7.25%)		 Nrs
Zhang et al, 201146 - SCZs: 46/206 (22.3%)
Controls: 38/615 (6.2%)
Argo et al, 201147 - SCZs: 22/192 (11.5%)
Kirkpatrick et al, 201248 SCZs: 3/64 (5%)
Controls: 0/85 (0%)		 Nrs
Morden et al, 201249 - SCZs: increased from 17.9% in 2000 to 26.8% in 2007 (16713/65362)
Controls: from 15.9% in 2000 to 26.5% in 2007
Schoepf et al, 201214 - SCZs: 77/679 (11.3%)
Controls: 5630/88778 (6.3%)
Schoepf et al, 201316 Overall DM:
SCZs: 283/1418 (19.95%)
Controls: 1494/14180 (10.53%)
T1DM:
SCZs: 36/1418 (2.5%)
Controls: 318/14180 (2.2%)		 SCZs: 247/1418 (17.4%)
Controls: 1211/14180 (8.5%)
Foley et al, 201450 - SCZs: 140/1155 (12.1%)
Foley et al, 201551 - SCZs: 11.2% current T2DM in schizophrenia (66/591)
Ingimarsson et al, 201752 - SCZs: 81/583 (13.9%)
Clozapine: 14.3% (27/188); never-on-clozapine: 13.7% (54/395).
Fang et al, 202453 - SCZs: 755/4606 (16.4%)
Controls: 475 (10.3%)
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Abbreviations: SCZs: Schizophrenic Patients, SMI: Severe Mental Illness, Nrs: Not reported separately, MHCs: Mental Health Clients.

Table 3.

Reported Risk Factors for Diabetes in Schizophrenia Patients (25 Studies)

Study/Year Risk Factors and Important Results
Dixon et al, 200023 Older age, lower educational attainment, female sex, and African-American race were associated with a greater likelihood of diabetes. Women had approximately 2.1-fold higher odds of diabetes.
Curkendall et al, 200415 The Prevalence of diabetes in SCZ patients in 2.1 (1.8–2.4) times higher than control population. The incidence of morbidity and mortality in SCZ patines increased 1.8 (1.2–2.6) by incidence of diabetes in these patients
Enger et al, 200425 Greater intensity of antipsychotic exposure was associated with a higher risk of new-onset diabetes. Overall, diabetes risk was approximately 1.75-fold higher among treated patients with schizophrenia and approximately threefold higher with more intensive exposure (>30% of observation days covered). Older age, pre-existing diabetes, and previous use of antianginal or antihypertensive medications were also associated with increased risk.
Feldman et al, 200427 All antipsychotics were associated with increased diabetes risk vs the general population. Highest risk was observed with thioridazine. Risperidone showed significantly higher risk vs haloperidol (RR 1.2, 95% CI 1.1–1.6). Quetiapine showed lower risk in patients aged 60–74 (RR 0.3, 95% CI 0.1–0.7). Clozapine had the highest incidence proportion overall (4.3%) and among patients ≥75 years (6.2%), although sample size was small.
Hung et al, 200529 Older age (60–69 Years old), longer duration of illness, obesity, family history of DM; no significant association with atypical antipsychotics
Lambert et al, 200530 Olanzapine (OR 1.36), clozapine (OR 1.34), and combination atypical therapy (OR 1.58) were associated with increased odds of T2DM. Dose-response relationship observed for olanzapine and clozapine. Hispanic ethnicity, African American ethnicity, ACE inhibitors, corticosteroids, beta-blockers, and thiazide diuretics were associated with higher diabetes risk. Risperidone and quetiapine were not significant in the main analysis.
Cohen et al, 200632 BMI >25 and age 30–49 years were reported as relevant factors. No significant association was found between long-term antipsychotic treatment and diabetes prevalence.
De Hert et al, 200633 Schizophrenia duration of more than 10 years, age >55 years, female sex, clozapine use, and higher BMI were associated with diabetes.
Osborn et al, 200631 Diabetes incidence increased 3.8 time in SMI patients
Olanzapine, clozapine
Barnett et al, 200634 Schizophrenia was included as an adjustment covariate, but no schizophrenia-specific diabetes risk factor was reported in the results; only corticosteroids vs PPIs significantly increased risk.
Suvisaari et al, 200835 Higher odds in schizophrenia were seen especially in females and older individuals; antipsychotic medication also increased odds of T2DM. The paper further notes higher odds with atypical antipsychotic use, cardiovascular medication, abdominal obesity, and lower handgrip strength.
Chien et al, 200936 Older age > 70 yo, Use of antipsychotics (amisulpride, zotepine), female gender, high-dose antipsychotic, living in urban areas
Bresee et al, 201038 Female gender, younger age (30–39 yo), lower socio-economic status
Nielsen et al, 201040 Higher age; initial olanzapine; mid-potency FGAs; antihypertensive drugs; lipid-lowering drugs; current low-potency FGAs, olanzapine, and clozapine increased diabetes risk; current aripiprazole reduced risk.
Okumura et al, 201039 Conventional antipsychotics, levomepromazine,
haloperidol, and zotepine, older age > 70 yo, male gender, higher BMI, longer duration of hospitalization
Argo et al, 201147 In the unadjusted analyses, diabetes was related to several factors, including advanced age, a waist-to-hip ratio above 1.0, physical inactivity, weekly working hours, hyperlipidemia, prior T2DM screening, elevated random blood glucose levels, and prolonged use of risperidone or olanzapine. After adjustment for potential confounders, sedentary behaviour, a waist-to-hip ratio of ≥1.0, and hyperlipidemia continued to show significant associations with diabetes.
Phutane et al, 201144 Patients receiving olanzapine had a significantly higher mean fasting plasma glucose than those receiving other antipsychotic medications: 97.8 (15.6) mg/dL vs 91.0 (7.4) mg/dL, respectively (t = 2.220; p = 0.03).
Zhang et al, 201146 Long-term clozapine treatment, Family history of diabetes, Higher BMI, Older age
Kirkpatrick et al, 201248 Lower socioeconomic status was reported as an important factor.
Schoepf et al, 201214 T2DM was identified as a predictor of mortality among patients with schizophrenia (RR = 2.2). The effect of diabetes on mortality was greater in patients with schizophrenia than in hospital controls (RR = 2.2 vs 1.1).
Schoepf et al, 201316 Among deceased patients with schizophrenia, T2DM was the most frequently documented comorbidity and contributed to 31.4% of hospital deaths. Only 14.4% of patients with schizophrenia and comorbid T2DM survived the study period.
Foley et al, 201450 Middle age (45–54 years), obesity, central obesity, treated hypercholesterolemia, treated hypertension, and a family history of diabetes were reported. Clozapine treatment was associated with increased T2DM risk, whereas olanzapine treatment was associated with decreased risk.
Foley et al, 201551 A family history of diabetes was associated with a family history of schizophrenia (OR = 1.58, 95% CI: 1.15–2.17), and the association became stronger after demographic adjustment (OR = 1.74). The authors concluded that schizophrenia and T2DM share familial risk factors.
Ingimarsson et al, 201752 Clozapine therapy was linked to an elevated risk of type 2 diabetes mellitus (T2DM) relative to control groups, with a more pronounced association observed in women (SMR = 4.4) than in men (SMR = 2.3). Among male patients, younger age was associated with blood glucose levels exceeding 13 mmol/L. However, after controlling for age and pre-existing T2DM, clozapine use was no longer significantly related to blood glucose levels above 13 mmol/L.
Fang et al, 202453 Female sex, younger age (<34 years), obesity, and the presence or absence of comorbidities were reported as relevant factors. Obesity was associated with greater risk among patients not receiving antipsychotic treatment. The likelihood of T2DM incidence was significantly higher in patients with schizophrenia who were not receiving antipsychotics (aHR = 2.83) than in non-schizophrenia controls and patients receiving antipsychotics (aHR ≤0.60). Antipsychotics did not alter the expression of hepatic gluconeogenesis genes but increased the expression of genes beneficial to glucose homeostasis in muscle cells.
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Characteristics of Selected Studies

A total of 35 studies were included in the review, comprising data from 139,304 individuals with schizophrenia across more than 52 countries worldwide. Participant numbers were incompletely reported in two studies. The included studies were published between 1998 and 2024.

Among the 35 included studies, 15 were cross-sectional, 4 were case-control, 6 were retrospective case-control, 8 were retrospective cohort, 1 was a cohort study, and 1 used a retrospective cohort–case-control design. Furthermore, 32 studies compared outcomes between patients with schizophrenia and control populations, encompassing approximately 3,774,448 participants in total. However, the number of individuals in the control group was not clearly reported in some studies (Table 1).

Overall Prevalence of Diabetes and Type 2 Diabetes in Patients with Schizophrenia

Thirty-four studies reported diabetes prevalence among patients with schizophrenia, with estimates ranging from 0% to 24.8%.22,42 One study specifically reported type 1 diabetes mellitus (T1DM), with a prevalence of 2.5%. Separately, 14 studies provided T2DM prevalence estimates, which ranged from 4.3% to 22.3%.40,46 In studies that reported diabetes without specifying its subtype, the reported prevalence was treated as overall diabetes prevalence and incorporated into the corresponding analysis.

Two separate quantitative analyses were undertaken. The first estimated the overall prevalence of diabetes mellitus and included all reported diabetes types. When a study reported only T2DM prevalence, that estimate was used as the overall diabetes prevalence for the pooled analysis. The second analysis was restricted to studies that reported T2DM prevalence separately.

Overall Diabetes Prevalence

A total of 33 studies were included in the meta-analysis of overall diabetes prevalence. Studies reporting only T2DM were also incorporated into this analysis using their reported T2DM prevalence as the overall diabetes estimate. The pooled prevalence of diabetes among patients with schizophrenia was 10.4% (95% CI: 8.3–12.9%).

Significant between-study heterogeneity was observed, as demonstrated by the Q test (P<0.05) and a very high I2 value of 99.49%. Egger’s regression test also indicated potential publication bias, with a statistically significant result (P<0.05; t = 3.70). The corresponding findings are shown in Figures 2 and 3.

Figure 2.

A forest plot of diabetes event rate in schizophrenia patients with wide study-to-study variation. The forest plot illustrates diabetes prevalence in schizophrenia patients, showing event rates and 95% confidence intervals for each study. The x-axis represents event rates from -1.00 to 1.00, while the y-axis lists studies from Makikyro et al, 1998 to Fang et al, 2024, plus a pooled estimate. Each study is marked with a dot and horizontal confidence interval. Event rates range from 0.006 to 0.268, with many around 0.10. The pooled estimate is 0.104, with a confidence interval from 0.083 to 0.129, depicted as a diamond near 0.10. Additional columns show ′Weight random′ and ′Residual′ values for each study.

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Total prevalence of all diabetes types in schizophrenia patients. Pink dots represent the Event Rate and 95% CI, as indicated at the top of the corresponding column.

Figure 3.

Text heavy statistical figure with funnel plot, Egger′s regression table and trim and fill table. A composite statistical figure with a funnel plot on the left, two results tables on the right and an interpretation text box along the bottom. The funnel plot is titled, Funnel Plot of Standard Error by Logit event rate. The x-axis label is Logit event rate, with tick labels negative 6, negative 5, negative 4, negative 3, negative 2, negative 1, 0, 1, 2, 3, 4, 5, 6. The y-axis label is Standard Error, with tick labels 0.0, 0.5, 1.0, 1.5, 2.0. Multiple open circles appear near the top of the plot and two diagonal boundary lines form a funnel shape meeting near the top center. A vertical line runs down the center. Near the bottom center, two diamond markers appear close together, labeled, Pooled effect left parenthesis Fixed effect right parenthesis and, Pooled effect left parenthesis Random effect right parenthesis. The upper right table is titled, Egger′s Regression Test and lists: Intercept left parenthesis bias right parenthesis, negative 9.17983; 95 percent CI, negative 14.23301 to negative 4.12664; t-value, 3.70506; df, 31; P-value left parenthesis 2-tailed right parenthesis, 0.00082. The lower right table is titled, Duval and Tweedie′s Trim and Fill Method. Under Fixed Effects, columns read Point Estimate and 95 percent CI. Rows read: Observed values, 0.20999, 0.20779 to 0.21220; Adjusted values, 0.20999, 0.20779 to 0.21220; Adjusted studies left parenthesis trimmed right parenthesis, 0, dash. Under Random Effects, columns read Point Estimate, 95 percent CI and Q Value. Rows read: Observed values, 0.10381, 0.08295 to 0.12919, 6257.544; Adjusted values, 0.10381, 0.08295 to 0.12919, 6257.544; Adjusted studies left parenthesis trimmed right parenthesis, 0, dash, dash. The bottom text box begins with, Interpretation: and reads, Egger′s test indicated potential publication bias left parenthesis p equals 0.00082 right parenthesis. The trim and fill method imputed 0 studies and the adjusted estimates were unchanged, suggesting that the results are robust to potential publication bias.

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Publication bias in meta-analysis for total diabetes prevalence. Pink lines and blue circles are components of the funnel plot, with the blue circles representing the individual studies and the red (pink) lines indicating the funnel plot boundaries. The blue and red diamonds represent the pooled estimates under the fixed-effect and random-effects models, respectively.

Type 2 Diabetes Mellitus Prevalence

A separate meta-analysis of 13 studies was conducted to estimate the prevalence of type 2 diabetes mellitus (T2DM). The results indicated that the prevalence of T2DM among individuals with schizophrenia was estimated at 13.2% (95% CI: 9.1–18.9%). Substantial heterogeneity was observed across studies, with a significant Q test (P<0.05) and an I2 value of 99.38%. Egger’s regression test indicated potential publication bias (P<0.05; t = 3.47). These findings are summarized in Figures 4 and 5.

Figure 4.

A forest plot of type 2 diabetes prevalence in schizophrenia, with study estimates and a pooled value. Type 2 Diabetes Prevalence in SCZ Patients: A forest plot displays 13 studies and a pooled estimate. The x-axis ranges from -1.00 to 1.00, with ticks at -0.50, 0.00 and 0.50. The y-axis is unlabeled. Study details include Event rate, Confidence intervals, Z-Value, p-Value, Relative weight and Std Residual. Event rates and limits: Dixon et al, 2000 (0.149, 0.125-0.177); Cohen et al, 2006 (0.090, 0.061-0.131); Barnett et al, 2006 (0.129, 0.110-0.151); Nielsen et al, 2010 (0.043, 0.039-0.048); Zhang et al, 2011 (0.223, 0.171-0.285); Argo et al, 2011 (0.115, 0.077-0.168); Morden et al, 2012 (0.268, 0.265-0.271); Schoepf et al, 2012 (0.113, 0.091-0.139); Schoepf et al, 2013 (0.174, 0.155-0.195); Foley et al, 2014 (0.121, 0.103-0.141); Foley et al, 2015 (0.112, 0.093-0.135); Ingimarsson et al, 2017 (0.139, 0.113-0.170); Fang et al, 2024 (0.164, 0.154-0.175). Pooled estimate: 0.132 (0.091-0.189), shown as a diamond. Relative weights: 7.26-7.89; Std Residuals: -1.65 to 1.19.

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Prevalence of type 2 diabetes in patients with schizophrenia. Pink dots represent the Event Rate and 95% CI, as indicated at the top of the corresponding column. The pink lines represent the corresponding 95% confidence intervals.

Figure 5.

A funnel plot of standard error versus logit event rate with pooled fixed and random effect markers. Funnel Plot of Standard Error by Logit event rate. A scatter funnel plot shows study points and funnel boundaries. The x-axis label is Logit event rate, ranging from minus 4 to 4 with increments of 1. The y-axis label is Standard Error, ranging from 0.0 to 0.4 with increments of 0.1, with 0.0 at the top and 0.4 at the bottom. About 12 open-circle study points appear between logit event rate about minus 3.2 and minus 0.2 and standard error about 0.02 to 0.22. The highest standard error points are near about minus 2.0 and minus 1.6 at about 0.20 to 0.22. Several points cluster near standard error about 0.08 to 0.12 and logit event rate about minus 1.6 to minus 0.8. Two slanted funnel boundary lines meet at the top near logit event rate 0 and standard error 0.0 and widen downward to about logit event rate minus 2 and plus 1 at standard error 0.4. A vertical center line runs at logit event rate 0. Two pooled-effect diamonds are plotted below the axis: pooled effect fixed effect at about logit event rate minus 0.4 and pooled effect random effect at about logit event rate minus 0.3. Egger′s Regression Test table lists: Intercept bias minus 10.73770; 95 percent confidence interval minus 17.40793 to minus 4.06747; t value 3.54313; df 11; P value 2 tailed 0.00461. Duval and Tweedie′s Trim and Fill Method table lists fixed effects observed values point estimate 0.24589 with 95 percent confidence interval 0.24289 to 0.24891; adjusted values point estimate 0.24589 with 95 percent confidence interval 0.24289 to 0.24891; adjusted studies trimmed 0. Random effects observed values point estimate 0.13220 with 95 percent confidence interval 0.09066 to 0.18881 and Q value 1943.95983; adjusted values point estimate 0.13220 with 95 percent confidence interval 0.09066 to 0.18881 and Q value 1943.95983; adjusted studies trimmed 0.

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Publication bias in meta-analysis for type 2 diabetes prevalence. Blue circles represent the individual studies, while the red (pink) lines indicate the funnel plot boundaries. The blue and red diamonds represent the pooled estimates under the fixed-effect and random-effects models, respectively.

Risk Factors for Diabetes in Patients with Schizophrenia

Across the 25 studies that reported risk factors, the development of diabetes in patients with schizophrenia was consistently associated with a combination of demographic, clinical, and treatment-related variables. The most frequently reported risk factors included older age, female sex, higher body mass index or obesity, family history of diabetes, longer duration of illness, lower socioeconomic status or education level, sedentary lifestyle, abdominal adiposity, and hyperlipidemia. Several studies also indicated that exposure to antipsychotic medications—particularly clozapine and olanzapine, as well as higher cumulative or high-dose antipsychotic exposure, was associated with an increased risk of diabetes. In addition, some studies reported associations with concomitant antihypertensive or lipid-lowering treatment, prior cardiovascular medication use, and ethnicity-related differences. Overall, these findings suggest that the risk of diabetes in schizophrenia is multifactorial and reflects the combined influence of baseline metabolic vulnerability, lifestyle factors, and antipsychotic-related metabolic effects.

Report of Publication Bias

Egger’s regression test indicated potential publication bias in both the overall diabetes and T2DM prevalence meta-analyses. However, the trim-and-fill analysis did not identify any missing studies, and the pooled prevalence estimates remained unchanged after adjustment. The observed funnel plot asymmetry may therefore reflect factors other than true publication bias, including substantial between-study heterogeneity, differences in study design, population characteristics, diagnostic criteria, and antipsychotic treatment patterns. Additionally, smaller studies reporting higher prevalence estimates may have been more likely to be published, contributing to small-study effects. Overall, while statistical evidence suggested possible publication bias, its impact on the pooled prevalence estimates appears to be limited.

Discussion

Across 35 studies involving more than 139,000 patients, the pooled prevalence of DM and T2DM was 10.4% and 13.2%, respectively. These findings confirm that metabolic disorders are highly prevalent in this population and reflect a combination of intrinsic vulnerability and treatment-related metabolic disturbances. Consistent risk factors identified across studies included older age, female sex, obesity or higher BMI, family history of diabetes, longer illness duration, lower socioeconomic status, and exposure to antipsychotic medications, particularly clozapine and olanzapine. Our findings align closely with previous systematic reviews. Vancampfort et al reported a global T2DM prevalence of approximately 11% in schizophrenia, which is comparable to our pooled estimate 13.2%.54 Similarly, Mitchell et al found that metabolic abnormalities were two to three times more common in schizophrenia than in the general population and diabetes prevalence was 2.1% in schizophrenia patients.55,56 Importantly, our review incorporates more recent studies, reflecting updated diagnostic criteria and contemporary antipsychotic prescribing patterns. Moreover, the elevated prevalence observed even in drug-naïve or minimally treated patients (eg, Verma 2009; Kirkpatrick 2012)37,48 supports the hypothesis of an intrinsic metabolic vulnerability, as previously suggested by some researchers.57,58 Furthermore, patients with severe mental illness (SMI) and co-occurring diabetes had a 77–88% higher risk of all-cause and cardiovascular mortality compared to diabetic patients without SMI.59 Given the multifactorial nature of diabetes risk in schizophrenia, preventive strategies must be comprehensive. These findings strongly support routine metabolic screening, particularly during the first year of antipsychotic treatment.60 Switching the antipsychotics with lower metabolic liability, such as aripiprazole, ziprasidone, or lurasidone, may reduce risk in high-risk patients.61,62 Emerging pharmacological approaches, including GLP-1 receptor agonists, may represent complementary strategies for improving weight management and glycemic control in patients with schizophrenia who are at increased metabolic risk.63 However, further real-world studies and clinical trials are needed to establish their long-term effectiveness, safety, and role in comprehensive metabolic management for this population. Non-pharmacological interventions, including structured exercise programs, nutritional counseling, and psychoeducation, have demonstrated meaningful improvements in weight and glycemic control.64 Integrating psychiatric and primary care services is essential to ensure continuous monitoring and timely intervention. Comprehensive lifestyle modification programs, including increased physical activity, dietary modification, smoking cessation, and weight reduction, should be integrated into the treatment plan for schizophrenia patients. Negative symptoms of schizophrenia, such as motivation, physical inactivity, and social withdrawal, are directly associated with sedentary lifestyle and poor dietary habits.65 Treating these negative symptoms through non-pharmacological approaches may indirectly reduce diabetes risk.

Limitations

This study should be interpreted considering the variability observed between studies and the potential for publication bias. The observed heterogeneity is likely related to the inclusion of studies from different geographic regions, healthcare settings, study designs, and patient populations. Differences in diagnostic approaches, clinical characteristics, disease duration, lifestyle factors, and antipsychotic treatment patterns may have contributed to this variability. To account for between-study differences, a random-effects model was applied, and the pooled estimates should be interpreted within the context of these variations. Furthermore, some included studies had incomplete reporting of participant characteristics and control group information, highlighting the need for more standardized reporting in future research.

Clinical Implications

The substantial diabetes burden necessitates routine metabolic screening, particularly during the first year of antipsychotic therapy. Clinicians are advised to select antipsychotics with lower metabolic liability, such as aripiprazole. Furthermore, integrating psychiatric and primary care is vital to deliver comprehensive lifestyle programs, including exercise, nutritional counseling, and non-pharmacological management of negative symptoms, to improve overall metabolic outcomes.

Conclusion

This systematic review and meta-analysis establishes a high pooled prevalence of diabetes mellitus (10.4%) and type 2 diabetes mellitus (13.2%) among individuals with schizophrenia. This elevated metabolic risk is multifactorial, driven by older age, female sex, obesity, family history, sedentary lifestyles, lower socioeconomic status, longer illness duration, and specific antipsychotic treatments like clozapine and olanzapine. Consequently, these findings highlight a critical need for routine metabolic screening and early preventive interventions to reduce long-term morbidity and mortality within this high-risk patient population. Further high-quality studies with standardized methodologies are needed to better clarify diabetes burden and sources of variability among patients with schizophrenia.

Acknowledgments

The authors acknowledge and appreciate the contributions of all researchers whose published work provided the evidence base for this systematic review and meta-analysis.

Funding Statement

No financial support was received from any organization, institution, or other funding source for the conduct of this study.

Registration Disclosure Statement

The review protocol was prospectively registered with PROSPERO (CRD420261465691), supporting transparency in the review process. In addition, the study protocol was registered at Kurdistan University of Medical Sciences under registration code IR.MUK.REC.1405.097.

Data Sharing Statement

All data generated or analyzed in this study are presented within the article and its cited references. Additional information may be obtained from the corresponding author upon reasonable request.

Author Contributions

Milad Jalilian: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Software; Supervision; Validation; Visualization; Writing – original draft; Writing – review and editing. Kimia Kake: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Software; Supervision; Validation; Visualization; Writing – original draft; Writing – review and editing. All authors took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no competing financial interests or personal relationships that could have influenced the conduct, analysis, interpretation, or reporting of this study.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

All data generated or analyzed in this study are presented within the article and its cited references. Additional information may be obtained from the corresponding author upon reasonable request.

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