The burden of schizophrenia in the middle east and north africa region, 1990–2019

ABSTRACT Schizophrenia ranks as the third-most common cause of disability among mental disorders globally. This study presents findings on the prevalence, incidence and years lived with

disability (YLDs) as a result of schizophrenia in the Middle East and North Africa (MENA), stratified by age, sex and sociodemographic index (SDI). We collected publicly accessible data from

the Global Burden of Disease (GBD) study 2019. This study reports the burden of schizophrenia, from 1990 to 2019, for the 21 countries that comprise MENA. In 2019, MENA exhibited an

age-standardised point prevalence of 248.2, an incidence rate of 14.7 and an YLD rate of 158.7 per 100,000, which have not changed substantially between 1990 and 2019. In 2019, the

age-standardised YLD rate was highest in Qatar and lowest in Afghanistan. No MENA countries demonstrated noteworthy changes in the burden of schizophrenia from 1990 to 2019. Furthermore, in

2019, the highest number of prevalent cases and the point prevalence were observed among those aged 35–39, with a higher prevalence among males in almost all age categories. Additionally, in

2019, the age-standardised YLD rates in MENA were below the worldwide average. Finally, there was a positive correlation between the burden of schizophrenia and the SDI from 1990 to 2019.

The disease burden of schizophrenia has remained relatively stable over the past thirty years. Nevertheless, as the regional life-expectancy continues to increase, the burden of

schizophrenia is also expected to rise. Therefore, early planning for the increase in the burden of the disease is urgently needed in the region. SIMILAR CONTENT BEING VIEWED BY OTHERS

INCIDENCE, PREVALENCE, AND GLOBAL BURDEN OF SCHIZOPHRENIA - DATA, WITH CRITICAL APPRAISAL, FROM THE GLOBAL BURDEN OF DISEASE (GBD) 2019 Article 27 July 2023 LONGITUDINAL TRENDS IN

SCHIZOPHRENIA AMONG OLDER ADULTS: A 12-YEAR ANALYSIS OF PREVALENCE AND HEALTHCARE UTILIZATION IN SOUTH KOREA Article Open access 27 February 2025 INCIDENCE, PREVALENCE, AND GLOBAL BURDEN OF

ADHD FROM 1990 TO 2019 ACROSS 204 COUNTRIES: DATA, WITH CRITICAL RE-ANALYSIS, FROM THE GLOBAL BURDEN OF DISEASE STUDY Article 08 September 2023 INTRODUCTION Schizophrenia is defined as a

cognitive and behavioral disorder that affects early brain development and manifests itself through several psychotic symptoms, including hallucinations, delusions, and disorganised behavior

and speech1. The prognosis for patients with schizophrenia can vary from making a full recovery to a lifelong need for care, and patients typically have a life expectancy which is roughly

twenty years less than that of the general population1,2. Psychiatric symptoms typically first appear during late adolescence or early adulthood, and suicidal behaviors are the most frequent

cause of death early in the course of the disease3. Schizophrenia has also been linked to several comorbid conditions, which is partially as a result of the high prevalence of drug abuse

and cigarette smoking, unhealthy lifestyles, and the potential impact of anti-psychotic medications on promoting obesity. These conditions predispose the patients to a higher rate of

metabolic syndrome, diabetes, cardiovascular disorders, and respiratory diseases4,5. In 2019, schizophrenia was the 42nd leading cause of disability among people of all ages and the 22nd

among individuals aged 25–49 years old6,7. The lifetime prevalence of schizophrenia has been estimated to be just below 1%8. In 2019, the global age-standardised prevalence of schizophrenia

was 287.4 per 100,000, and this rate was approximately the same as in 19906. Also in 2019, schizophrenia accounted for 12.1% of all disability-adjusted-life-years (DALYs) attributable to

mental disorders, and was surpassed only by depressive (37.4%) and anxiety (22.9%) disorders6. The highest incidence of schizophrenia was found in those aged 20–24, with no significant

sex-based differences in the incidence rate9. Several reports have been published in recent years discussing mental disorders, and more specifically the burden of schizophrenia at the

regional level and across the world6,9,10,11,12,13. However, none of these articles have exclusively focused on the attributable burden of schizophrenia in the Middle East and North Africa

(MENA) region. The countries located in MENA vary considerably in terms of socioeconomic profile, health system coverage and capacities, and healthcare infrastructures and provisions14,15.

During the past three decades, the MENA region has witnessed several enhancements in health outcomes, resulting in rising life expectancies and decreased neonatal mortality16. Consequently,

in parallel with increasing longevity, it is expected that the prevalence of chronic conditions, such as mental disorders, will continue to grow in MENA. Furthermore, as a stigmatized

disease, schizophrenia is often overlooked among affected patients, especially in developing countries. Moreover, as the socioeconomic status of a country decreases the stigma of mental

disorders increases, potentially leading to an underestimation of the burden of schizophrenia in lower socio-economic countries. Therefore, investigating the epidemiology of schizophrenia in

the MENA region is of paramount interest17. Consequently, this study utilized data from the Global Burden of Disease (GBD) study 2019 to present the burden of schizophrenia in MENA from

1990 to 2019, stratified by sex, age and socio-demographic index (SDI). METHODS The Global Burden of Disease (GBD) study, which was established by the Institute of Health Metrics and

Evaluation (IHME), measures the burden of diseases and injuries in over 200 countries and territories. Although schizophrenia is a relatively common mental problem, its burden has not been

quantified across all global regions. Therefore, this study presents an assessment of the burden of schizophrenia from 1990 to 2019 for all countries in MENA. There are 21 countries in MENA,

which are: Afghanistan, Algeria, Bahrain, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Saudi Arabia, Sudan, the Syrian Arab Republic, Tunisia, Turkey,

the United Arab Emirates and Yemen. A full description of the methodology utilised by IHME to model the burden of disease has been previously described7,16,18. The GBD 2019 estimates, which

cover the period 1990–2019, are available at the following links: http://ghdx.healthdata.org/gbd-results-tool and https://vizhub.healthdata.org/gbd-compare/. CASE DEFINITION AND DATA

SOURCES Schizophrenia is a serious mental disorder which is characterised by a large number of symptoms, including: delusions, hallucinations, diminished interest, flat affect, thought

disorders, and emotional withdrawal. The GBD disease modelling process only included data from studies that diagnosed schizophrenia using either the Diagnostic and Statistical Manual of

Mental Disorders (DSM) criteria (DSM-IV-TR: 295.10-295.30, 295.60, 295.90) or the International Classification of Diseases (ICD) criteria (ICD 10: F20). The diagnostic criteria encompass the

following key elements: (1) Presence of at least two of the following symptoms, each enduring for a substantial part of a one-month period (a shorter duration if effectively treated): (i)

Delusions, (ii) Hallucinations, (iii) Disorganised speech (e.g., frequent incoherence or derailment), (iv) Markedly disorganised or catatonic behavior, (v) Negative symptoms (i.e., affective

flattening, alogia, or avolition); (2) Dysfunction at work and socially; (3) Persistence of the disorder’s signs and symptoms for a duration of six months or more; (4) Exclusions included

substance abuse, schizoaffective and mood disorders, and/or general medical conditions, as well as any connection to pervasive developmental disorders7. IHME conducted a systematic review

for schizophrenia, which encompassed searching the scientific literature (i.e., PsycInfo, Embase, and PubMed), examining the grey literature, and consultation with an expert. As part of the

GBD project, the electronic databases are searched biennially for mental disorders, including schizophrenia. The last systematic review for schizophrenia was carried out in GBD 2017, with

the next review being due in GBD 2020. However, consulting the expert and searching the grey literature produced new data sources in GBD 20197. The inclusion criteria applied were as

follows: (1) published after 1980; (2) cases were defined using DSM or ICD criteria; (3) inclusion of sufficient methodological details and sample characteristics for assessing study

quality; and (4) samples that represented the general population. Specifically excluded were samples from inpatients or pharmacological treatments, case studies, veterans, or refugee cases.

There were no constraints placed on the publication language. The data sources utilised to model the schizophrenia burden are accessible at this website:

https://ghdx.healthdata.org/gbd-2019/data-input-sources7. DATA PROCESSING AND DISEASE MODEL When necessary, the data extraction process involved three different age and sex splitting

procedures: (1) The available estimates were divided into specific five-year age groups by sex. For example, in studies which reported the prevalence in broad age ranges separately for males

and females (e.g., 15–65 year old men and women individually), and in cases where studies had smaller age groups without sex separation (e.g., prevalence among 15 to 29 year olds, then in

30 to 70 year olds, for both sexes combined), the sex ratios reported and uncertainty ranges were used to divide the age specific estimates by sex. (2) Meta-Regression with Bayesian priors,

Regularisation, and Trimming (MR-BRT) was used to split the remaining data. This method involved matching sex-specific estimates for each parameter, according to location, age, and year.

MR-BRT regression was then employed to model the pooled sex ratios, along with their associated uncertainty bounds. These pooled sex ratios were then utilised to split the estimates in the

dataset. The prevalence ratio between males and females was 1.17 (95% uncertainty interval (UI) 0.60–1.75). 3. For prevalence estimates covering age categories spanning 25 years or more, the

age pattern estimated by DisMod-MR 2.1 was used to split the data into five-year age groups. It’s important to note that the DisMod-MR model used for estimating the age pattern did not

contain any previously age split data7. IHME utilised DisMod MR 2.1, using the standard GBD 2019 decomposition structure, to estimate the data related to schizophrenia. At each stage of the

decomposition process, IHME compared the new model with the best model from GBD 2017 and the best model from the previous stage. If substantial differences were observed between models,

these variances were thoroughly explored and elucidated. In cases where it was deemed necessary, adjustments were implemented to the dataset or the model priors. When outliers were

identified, they were included or excluded based upon a re-examination of their quality and methodology. Initially, all epidemiological parameters were integrated into the modelling process.

It was believed, based on the literature on schizophrenia and discussion with the expert that no cases of schizophrenia occurred before the age of 10 or after the age of 80. Furthermore,

the remission rate was restricted to a maximum of 0.04, in line with the data in the dataset. In areas lacking available data, prevalence estimates were informed by location-level

covariates. Only one location-level covariate, lag distributed income (LDI), was utilised to model the prevalence of schizophrenia. COMPILATION OF RESULTS The two sequelae (acute and

residual) of schizophrenia, along with their corresponding disability weights (DWs), can be found in Table S1. To calculate the years lived with disability (YLDs), the prevalence estimates

for each sequela were multiplied by their respective DWs. The YLDs and DALYs were the same, since there was no mortality due to schizophrenia. All estimates were standardised using the GBD

standard population. 95% uncertainty intervals (UIs) were included with all estimates and were generated by producing 1000 iterations at each stage of the estimation process. The final

estimates represented the mean values over the 1000 iterations, and the 95% UIs were indicated as the 25th and 975th values among the numerically ordered iterations. Smoothing Spline

models19 was employed to investigate the relationship the socio-demographic index (SDI) has with the burden of schizophrenia. The SDI is a composite model that contains per capita income,

mean number of years attending school (aged 15 and above), and the fertility rate in women aged 25 or less. The SDI ranges from 0 to 1, representing the spectrum from the lowest to the

highest development level7. The estimates for the point prevalence and annual incidence were obtained from the GBD website (http://ghdx.healthdata.org/gbd-results-tool) and all visual

representations were created with R software (Version 3.5.2). ETHICS APPROVAL AND CONSENT TO PARTICIPATE The present study was approved by Ethics Committee of Shahid Beheshti University of

Medical Sciences, Tehran, Iran (IR.SBMU.RETECH.REC.1401.387). RESULTS THE MIDDLE EAST AND NORTH AFRICA REGION In 2019, there were 1.6 million (95% UI: 1.3 to 1.9) prevalent cases of

schizophrenia. In addition, the age-standardised point prevalence was 248.2 (203.9 to 294.9) per 100,000, which has hardly changed since 1990 [0.5% (-1.2 to 2.0)] (Tables 1 and S2). There

were 97.7 thousand (79.8 to 119.7) incident cases of schizophrenia in 2019, with an age-standardised rate of 14.7 (12.1 to 17.9) per 100,000, which did not differ from 1990 [− 1% (− 2.7 to

0.7)] (Tables 1 and S3). A total of 1.0 million (0.7 to 1.3) YLDs were attributable to schizophrenia in 2019, having an age-standardised rate of 158.7 (113.2 to 207.8) YLDs per 100,000

population. This rate also has not changed since 1990 [0.4% (− 2.2 to 3.1)] (Tables 1 and S4). COUNTRY LEVEL The age-standardised point prevalence of schizophrenia varied from 217.8 to 285.0

cases per 100,000 in the region. Qatar [285.0 (225.4 to 351.1)], the United Arab Emirates [275.3 (218.5 to 337.2)] and Kuwait [273.8 (216.4 to 334.0)] were the three highest in 2019.

Conversely, Afghanistan [217.8 (176.2 to 266.6)], Yemen [225.7 (180.7 to 273.9)] and Sudan [232.7 (186.1 to 284.0)] were the three lowest (Table S2). Figure 1A presents the age-standardised

point prevalence estimates of schizophrenia by country, separately for men and women, in 2019. The age-standardised incidence rate of schizophrenia in 2019 varied from 14.0 to 16.2 cases per

100,000 in the region. Qatar [16.2 (12.9 to 20.3)], the United Arab Emirates [15.7 (12.5 to 19.5)] and Kuwait [15.5 (12.4 to 19.3)] had the highest rates, with the lowest being in

Afghanistan [14.0 (11.3 to 17.1)], Yemen [14.2 (11.4 to 17.4)] and Sudan [14.3 (11.7 to 17.7)] (Table S3). Figure 1B presents the age-standardised incidence rates of schizophrenia by

country, separately for males and females, in 2019. The age-standardised YLD rate of schizophrenia in 2019 ranged from 135.6 to 182.5 cases (per 100,000) in the region. Qatar [182.5 (125.7

to 245.0)], the United Arab Emirates [176.5 (123.7 to 235.0)] and Kuwait [175.6 (121.0 to 234.3)] had the highest rates, while Afghanistan [135.6 (96.4 to 180.8)], Yemen [143.3 (100.6 to

191.3)] and Sudan [149.1 (104.2 to 199.5)] were lowest (Table S4). Figure 1C presents the age-standardised YLD rates of schizophrenia by country, separately for males and females, in 2019.

The age-standardised prevalence, incidence and YLD rates of schizophrenia did not change significantly in any MENA countries from 1990 to 2019 (Tables S2–S4). The changes in the

age-standardised incidence, prevalence, and YLD rates for each country are depicted in Fig. 2A–C, broken down by sex, for the period 1990–2019. AGE AND SEX PATTERNS The total number of

prevalent cases and the prevalence estimates in 2019 increased sharply for both sexes, starting from the 10–14 age range, reaching their highest level in those aged 35–39, before decreasing

with age (Fig. 3A). Similarly, the number of incidence cases and the incidence rates began to rise from the 10–14 age range, for both sexes, were highest in the 20–24 age range and then

declined with age (Fig. 3B). Furthermore, the YLD numbers rose with increasing age in both sex groups and peaked in those aged 30–34 years old, and then reduced with age. The pattern was

similar for the YLD rate, but in both sexes the highest rate was seen in those aged 35–39 years old (Fig. 3C). Males had a higher prevalence, incidence and YLD cases in all age categories.

Likewise, males had higher prevalence, incidence and YLD rates of schizophrenia up to 80–84 years old, while the prevalence and YLD rates were higher for females in all remaining age groups.

The schizophrenia associated YLD rates in 2019 were below the global rates for both sexes over 20 years of age (ratio of MENA/global YLD rate < 1). For both sexes, people aged 10–19

years of age exhibited YLD rates that were close to the global rate (ratio of MENA/global YLD rate = 1). The YLD rate in females aged 80 and older was 0.7 times the global rate in 2019.

Furthermore, in 2019 males had similar YLD ratios (ratio of MENA/global YKD rate = 1), to those in 1990, in most age groups except for 15–19, 40–44 and 95+ years old, which had higher ratios

than in 1990. Similarly, in 2019 the YLD ratios (ratio of MENA/global YLD rate = 1) for females increased in the 15–19, 75–79 and older than 90 age-groups, compared to 1990, while all other

age-groups had similar rates (Fig. 4). RELATIONSHIP WITH SOCIO-DEMOGRAPHIC INDEX (SDI) An almost linear positive association was evident between SDI and the YLD rate of schizophrenia

between 1990 and 2019. In general, countries located within the region exhibited a steady rise in YLD rates, from 1990 to 2019, with increases in their SDIs. Qatar was the only country that

had actual rates that were higher than those expected from 1990 to 2019, while all other countries had rates below the expected level (Fig. 5). DISCUSSION This article presents an analysis

of the burden of schizophrenia in MENA, encompassing the prevalence, incidence, and YLDs, using the most recent GBD 2019 data. This study is the first to present current information on the

regional and national burden of schizophrenia in the MENA region. Previous studies were either been restricted to an individual country or investigated multiple causes with limited

epidemiological data. According to the latest research on the global burden of mental diseases, schizophrenia affects far fewer patients than several other mental conditions, but the YLDs

attributable to this disorder are amongst the highest of these conditions6. Schizophrenia presents with a wide range of clinical symptoms and signs, and also varies greatly in the severity

level. Schizophrenia requires lifelong treatment, which is demanding for both the patients and their families. Furthermore, some patients may develop resistance to conventional therapies, as

their condition exacerbates with more frequent relapses20. These patients are also at a higher risk of suicide attempts and assault, further impacting the patient, their family, and their

caregivers21,22. Due to economic crises, rapid population growth, a shortage of healthcare staff, weak coverage, political issues, and the stigmatizing attitudes of the general population

against mental illnesses, many of the healthcare systems in the MENA region are yet to reach their full potential and provide acceptable standards of care. As a result, mismanagement,

misdiagnosis, or missed cases might commonly occur23. Thus, the true burden of schizophrenia and the disability it imposes is expected to be far higher than the estimates reported here. Drug

abuse, alcoholism, and smoking are common in schizophrenic patients, which can lead to comorbidities such as malnutrition, diabetes, vascular events, blood-borne infections, and chronic

obstructive pulmonary disease (COPD), causing additional disability and mortality24. Although these comorbidities have a global importance, the impact is even larger in economically troubled

healthcare systems, which is the situation in many MENA countries. Taken together, to alleviate the burden of schizophrenia, there is an urgent need for a plan to solve the widening

socioeconomic disparities and implement measures to reduce the stigma associated with schizophrenia as soon as possible. In line with the global trend for schizophrenia, the age-standardised

prevalence, incidence, and YLDs in the region did not vary significantly between 1990 and 20196. In general, countries which had higher age-standardised prevalence also had higher

age-standardized incidence, and YLDs (i.e., Qatar, United Arab Emirates, and Kuwait). This same pattern was also the case for the countries which showed the lowest rates (i.e. Afghanistan,

Yemen, and Sudan). Moreover, schizophrenia is linked to decreased fertility in both sexes, with males experiencing a more pronounced impact25. This can be attributed to the behavioral and

social characteristics associated with schizophrenia. It is anticipated that decreased fertility will increase due to the ongoing delayed marriage patterns, even though the age of onset for

schizophrenia will remain unchanged26. Natural selection is expected to reduce the population frequencies of genes associated with reduced fertility. Nonetheless, the prevalence of

schizophrenia continues to be high, not only in the MENA region but also globally, with the frequency of the disease showing no significant change in recent decades27. This is commonly known

as a "Darwinian paradox"26. Multiple hypotheses have been proposed to explain how schizophrenia evades the influence of natural selection, but the exact mechanism remains an

enigma28,29,30. A plausible explanation for the unchanged prevalence of schizophrenia, despite its association with decreased fertility, is that the genetic factors contributing to

schizophrenia may also confer advantages related to the development of essential human characteristics, including language, complex cognitive skills, and other favorable brain functions31.

This hypothesis is substantiated by the presence of enhanced recent evolutionary markers near the loci linked to schizophrenia31,32. However, the evolutionary puzzle of schizophrenia remains

complex and requires further research to be fully understood. As illustrated in Fig. 2A–C, the highest incidence of schizophrenia was observed in the 15 to 39 age group, and the disease’s

prevalence peaked among those aged 20 to 54 years old, after which it gradually decreased with increasing age. The peak incidence starts earlier in life (20 to 24 age group) and the

prevalence peaks in the 35 to 39 age group, and then reduces with age. This pattern was also seen for the YLD rates. The presented data emphasises the need for screening and intervention

before the peak ages in the incidence, and also underlines the increased need for social, mental, and healthcare support during the peaks in the prevalence and YLDs. As the disease gets more

chronic, and particularly when accompanied by more frequent relapses (either due to the nature of the disease or by mismanagement), more YLDs are observed and thus more access to medical

care and social support is required to prevent treatment resistant conditions and worse outcomes, such as suicide, overdose, or domestic violence33. In almost all age groups, men showed

higher prevalence, incidence and YLD values and rates, but these differences were not statistically significant. The changes in incidence, prevalence, and YLDs observed in both sexes

generally show a decrease from 1990 to 2019 in most countries. Interestingly, the percentage changes in the incidence were negative in all MENA countries. Nevertheless, none of the changes

were statistically significant, and thus should be carefully interpreted with regards to future planning and policy making. The MENA YLD rates were below those found globally for all age

groups, with the exception of those aged 10 to 19 year olds. This can be explained through the vast medical and non-medical problems faced by most countries in MENA. The burden of

communicable diseases are substantially higher in MENA, than globally, and thus chronic conditions such as mental disorders might not receive the appropriate priority level for their

management and treatment34. Furthermore, the burden of schizophrenia remained unchanged from 1990 to 2019 in most age groups, except for the elderly ages, which have increased. As displayed

in Fig. 4, SDI has a positive linear relationship with the age-standardised YLD rate in MENA. These results should be carefully interpreted as there are major gaps between the countries

showing the lowest values and those with the highest. Countries such as Afghanistan, Yemen, and Sudan were embroiled in prolonged conflicts during much of the measurement period, and their

healthcare systems have been severely affected by their unbalanced economies and political problems35,36. Consequently, the low burden of schizophrenia in these countries is likely to be

highly biased and artificially underestimated. In contrast, economically stable and high-income countries in this region have shown a higher burden of schizophrenia, which can be attributed

to their more efficient healthcare systems and screening strategies. An alternative explanation for this finding might be that the high level of urbanisation and high density housing in the

high income countries is related to the higher incidence of schizophrenia, due to elevated levels of stress and pollution in these areas37,38. While GBD continues to improve on the data and

methodologies for estimating the burden of mental disorders, including schizophrenia, several challenges need acknowledging. Firstly, there were a large number of locations without

high-quality raw data. Secondly, quantifying and eliminating all variation caused by measurement error in our prevalence estimates is a challenging task. Although IHME has refined the

methodology to address known sources of bias (e.g., case definitions or survey methods), there are still very few data points available to inform such adjustments. Additionally, there is a

paucity of research on the risk factors of mental disorders which can be used as predictive covariates in our epidemiological models39. CONCLUSION The present article highlights the

importance of cautiously interpreting the currently available epidemiological information on the burden of schizophrenia in MENA, since the gathered data are prone to several biases. Thus,

presumably the low burden of this condition might increase substantially in the future, as the healthcare systems start to screen and identify more patients. The most important aspect in

preventing any future rise in the burden of schizophrenia lies in the efficient screening and prompt identification of patients, and then effectively treating these patients using a holistic

approach. By reducing the prevalence of this mental condition, the burden of its related comorbidities and problems will also be addressed, significantly contributing to the overall health

of the communities and the countries. Finally, it is important not to underestimate the significance of stigma directed towards people with psychiatric disorders. Initiatives aimed at

increasing awareness about schizophrenia among patients, their families and their social networks can contribute significantly to reducing the disability associated with the disease. DATA

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predictors of schizophrenia in Nordic registers. _Psychol. Med._ 48(7), 1201–1208 (2017). Article  PubMed  PubMed Central  Google Scholar  Download references ACKNOWLEDGEMENTS We would like

to thank the Institute for Health Metrics and Evaluation staff and its collaborators who prepared these publicly available data. We would also like to thank the Clinical Research Development

Unit of Tabriz Valiasr Hospital, Tabriz University of Medical Sciences, Tabriz, Iran for their assistance in this research. FUNDING The Bill and Melinda Gates Foundation, who were not

involved in any way in the preparation of this manuscript, funded the GBD study. The Shahid Beheshti University of Medical Sciences, Tabriz, Iran (Grant No. 43002510) also supported the

present report. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Neurosciences Research Center, Aging Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran Saeid Safiri *

Clinical Research Development Unit of Tabriz Valiasr Hospital, Tabriz University of Medical Sciences, Tabriz, Iran Saeid Safiri * Student Research Committee, School of Medicine, Iran

University of Medical Sciences, Tehran, Iran Maryam Noori * HIV/STI Surveillance Research Center, WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health,

Kerman University of Medical Sciences, Kerman, Iran Seyed Aria Nejadghaderi * Systematic Review and Meta-analysis Expert Group (SRMEG), Universal Scientific Education and Research Network

(USERN), Tehran, Iran Seyed Aria Nejadghaderi * Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran Ali Shamekh * Department of Life and Health Sciences,

University of Nicosia, Nicosia, Cyprus Mark J. M. Sullman * Department of Social Sciences, University of Nicosia, Nicosia, Cyprus Mark J. M. Sullman * Centre for Statistics in Medicine,

NDORMS, Botnar Research Centre, University of Oxford, Oxford, UK Gary S. Collins * NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK Gary

S. Collins * Social Determinants of Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran Ali-Asghar Kolahi Authors * Saeid Safiri View author publications You

can also search for this author inPubMed Google Scholar * Maryam Noori View author publications You can also search for this author inPubMed Google Scholar * Seyed Aria Nejadghaderi View

author publications You can also search for this author inPubMed Google Scholar * Ali Shamekh View author publications You can also search for this author inPubMed Google Scholar * Mark J.

M. Sullman View author publications You can also search for this author inPubMed Google Scholar * Gary S. Collins View author publications You can also search for this author inPubMed Google

Scholar * Ali-Asghar Kolahi View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS SS and AAK designed the study. SS analysed the data and

performed the statistical analyses. SS, MN, SAN, AS, MJMS, GSC, and AAK drafted the initial manuscript. All authors reviewed the drafted manuscript for critical content. All authors approved

the final version of the manuscript. CORRESPONDING AUTHORS Correspondence to Saeid Safiri or Ali-Asghar Kolahi. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing

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permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Safiri, S., Noori, M., Nejadghaderi, S. _et al._ The burden of schizophrenia in the Middle East and North Africa region, 1990–2019. _Sci Rep_

14, 9720 (2024). https://doi.org/10.1038/s41598-024-59905-8 Download citation * Received: 12 July 2023 * Accepted: 16 April 2024 * Published: 27 April 2024 * DOI:

https://doi.org/10.1038/s41598-024-59905-8 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a shareable link is not

currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative KEYWORDS * Schizophrenia * Middle East and North Africa *

Prevalence * Epidemiology * Incidence