Prevalence of type 2 diabetes mellitus in the general population of Saudi Arabia, 2000–2020: A systematic review and meta-analysis of observational studies

Jarrar, Mu’taman; Abusalah, Mai Abdel Haleem; Albaker, Waleed; Al‐Bsheish, Mohammad; Alsyouf, Adi; Al-Mugheed, Khalid; Issa, Marwan Rasmi; Alumran, Arwa

doi:10.4103/sjmms.sjmms_394_22

Cited by 31 publications

(19 citation statements)

References 42 publications

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“…Relevant research have shown that males often postpone going to the doctor when they are ill and use the less extensive array of healthcare services ( 85 ). Women are more likely than males to seek medical attention when they are unwell, which increases the likelihood that their condition will be discovered ( 86 , 87 ). Moreover, the impact of cultural expectations and societal norms on gender-specific health behaviors cannot be overlooked.…”

Section: Discussionmentioning

confidence: 99%

An updated systematic review and Meta-analysis of the prevalence of type 2 diabetes in Iran, 1996–2023

Hazar,

Jokar,

Namavari

et al. 2024

Front. Public Health

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BackgroundDiabetes mellitus (DM) poses a significant threat to public health, and the anticipated surge of over 100% in the age-standardized prevalence of type 2 diabetes in Iran between 2021 and 2050 underscores the pressing need for focused attention. The rationale for estimating the prevalence of type 2 diabetes in Iran becomes even more compelling when considering the potential cascading effects on the healthcare system, quality of life, and economic burden. The aim of this study was to estimate the prevalence and trends of DM from 1996 to 2023 in the Islamic Republic of Iran.MethodsUp to July 2023, without deadlines, the search for appropriate articles in Persian and English. Iranian sources including SID, Magiran, and Element were included in the databases, along with foreign ones like PubMed/MEDLINE, Web of Science, Science Direct, Embase, Scopus, ProQuest, and Google Scholar. Using the JBI quality checklist, the study’s level of quality was evaluated. Version 14 of STATA was used to carry out the statistical analysis. The Dersimonian and Liard random-effects models were used because of heterogeneity. To investigate the causes of heterogeneity, subgroup analysis and univariate meta-regression were utilized. Sensitivity analysis was then carried out to see how each study’s findings affected the final findings. The prevalence pattern over time was also followed using cumulative meta-analysis.ResultsThere were 53 studies in all, with a combined sample size of 1,244,896 people. Men were predicted to have a type 2 diabetes prevalence of 10.80% (95% CI: 9.1–12.4), while women were assessed to have a prevalence of 13.4% (95% CI: 11.6–15.3). Additionally, the prevalence of diabetes was much higher in the 55–64 age group, coming in at 21.7% (95% CI: 17.5–25.0). The anticipated prevalence of diabetes was 7.08% for 1988 to 2002, 9.05% for 2003 to 2007, 9.14% for 2008 to 2012, 15.0% for 2013 to 2017, and 13.40% for 2018 to 2023, among other time periods. Geographically, type 2 diabetes was most prevalent in Khuzestan (15.3%), followed by Razavi Khorasan (14.4%), Qazvin (14.3%), and Yazd (12.6%).ConclusionThe prevalence of type 2 diabetes was estimated at 10.8%, highlighting variations across gender, age groups, and geographic regions that underscore the necessity for specific interventions. These findings advocate for proactive measures, including tailored screening and lifestyle modification programs. The notable temporal increase from 2013 to 2017 signals the need for policymakers and healthcare practitioners to develop effective strategies, anticipating and addressing the potential future burden on the healthcare system.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023437506, identifier: CRD42023437506.

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Section: Discussionmentioning

confidence: 99%

An updated systematic review and Meta-analysis of the prevalence of type 2 diabetes in Iran, 1996–2023

Hazar,

Jokar,

Namavari

et al. 2024

Front. Public Health

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“…Unlike the A1C, literature about RIs on hemoglobin subfractions for healthy individuals is scarce. Although it is well recognized that RIs may vary from one population to another, it is important that these parameters are established for the Saudi population, which is already known to have a high prevalence of diabetes [ 44 ]. In addition to this, consanguineous marriage is very common in Saudi populations.…”

Section: Introductionmentioning

confidence: 99%

Establishment of reference interval for hemoglobin A1C and other hemoglobin subfractions for healthy Saudi adults

Borai,

Ichihara,

Bahijri

et al. 2024

PLoS ONE

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Background The establishment of Reference Intervals (RIs) for Hemoglobin A1C and other hemoglobin subfractions (A1A, A1B, F, LA1C, A0) is of utmost importance in screening, diagnosing, and monitoring diabetes and other hemoglobin abnormalities through the application of high-pressure liquid chromatography (HPLC) technique. Because there are no locally established RIs for these parameters, it is essential to establish RIs specific to the Saudi population to accurately diagnose and monitor diabetic individuals and identify abnormal levels in hemoglobin subfractions. Methods As part of the IFCC global multicenter study of laboratory reference values, a cross-sectional study was conducted in Saudi Arabia. The study involved recruiting a total of 381 healthy adult subjects (>18 years, BMI 28.3 ± 6 kg/m2). Blood samples were analyzed for A1C, biochemical and other immunoassay parameters. The need for RIs based on sex, age, and BMI was determined using the standard deviation ratio (SDR) through a 3-level nested ANOVA. Results Based on the threshold of SDR≥0.4, RIs for A1C and other Hb subfractions were not partitioned by sex or BMI, but partitioned by age (<45 & ≥45 years) for A1C, LA1C, A0 and F. Spearman’s correlation between glucose, insulin, and C-peptide showed a positive association with different hemoglobin subtractions of A1B, F, A1C, and LA1C. The RIs were obtained by using the parametric method and the latent abnormal values exclusion (LAVE) principle was applied on A1C. Conclusion This study established RIs for A1C and other Hb subfractions for healthy adult Saudis. Age was found to be an important source of variation for most of the parameters including A1C. These findings will enhance the understanding and clinical decision-making concerning A1C and other hemoglobin subfractions. The elevated upper limit of RIs for A1C reflects the high prevalence of diabetes in the Saudi population specially in those with increased age.

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“…Advanced age and well-known susceptibility genes, such as the APOE gene encoding apolipoprotein E (ApoE), remain the most significant non-modifiable risk factors for AD ( Al-Hamdan et al, 2010 ; Walker et al, 2017 ; Jarrar et al, 2023 ). Based on numerous epidemiological studies, several modifiable vascular and metabolic factors have been linked to increasing the risk of cognitive impairment and AD, such as midlife hypertension, stroke, midlife diabetes, hyperlipidemia, obesity, and depression, in addition to other lifestyle risk factors including smoking, sleep disturbances, and low levels of education ( Al-Shammari and Al-Subaie, 1999 ; Saeed et al, 2011 ; Bennett and Thomas, 2014 ; Levin and Vasenina, 2019 ; Andreescu and Lee, 2020 ; Kuring et al, 2020 ; Tinnirello et al, 2021 ; Zhao et al, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

“…In the Kingdom of Saudi Arabia (KSA), the aging population is growing, with people aged more than 60 years, around 1.3 million in 2016. The number is expected to rise and reach more than 10 million by 2050 ( Jarrar et al, 2023 ), substantially increasing financial and emotional burdens on families and caregivers. Additionally, the lack of early detection and accurate diagnosis of neurocognitive disorders in adults is considered an issue that needs to be addressed.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence approaches for early detection of neurocognitive disorders among older adults

AlHarkan,

Sultana,

Al Mulhim

et al. 2024

Front. Comput. Neurosci.

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IntroductionDementia is one of the major global health issues among the aging population, characterized clinically by a progressive decline in higher cognitive functions. This paper aims to apply various artificial intelligence (AI) approaches to detect patients with mild cognitive impairment (MCI) or dementia accurately.MethodsQuantitative research was conducted to address the objective of this study using randomly selected 343 Saudi patients. The Chi-square test was conducted to determine the association of the patient’s cognitive function with various features, including demographical and medical history. Two widely used AI algorithms, logistic regression and support vector machine (SVM), were used for detecting cognitive decline. This study also assessed patients’ cognitive function based on gender and developed the predicting models for males and females separately.ResultsFifty four percent of patients have normal cognitive function, 34% have MCI, and 12% have dementia. The prediction accuracies for all the developed models are greater than 71%, indicating good prediction capability. However, the developed SVM models performed the best, with an accuracy of 93.3% for all patients, 94.4% for males only, and 95.5% for females only. The top 10 significant predictors based on the developed SVM model are education, bedtime, taking pills for chronic pain, diabetes, stroke, gender, chronic pains, coronary artery diseases, and wake-up time.ConclusionThe results of this study emphasize the higher accuracy and reliability of the proposed methods in cognitive decline prediction that health practitioners can use for the early detection of dementia. This research can also stipulate substantial direction and supportive intuitions for scholars to enhance their understanding of crucial research, emerging trends, and new developments in future cognitive decline studies.

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Prevalence of type 2 diabetes mellitus in the general population of Saudi Arabia, 2000–2020: A systematic review and meta-analysis of observational studies

Cited by 31 publications

References 42 publications

An updated systematic review and Meta-analysis of the prevalence of type 2 diabetes in Iran, 1996–2023

An updated systematic review and Meta-analysis of the prevalence of type 2 diabetes in Iran, 1996–2023

Establishment of reference interval for hemoglobin A1C and other hemoglobin subfractions for healthy Saudi adults

Artificial intelligence approaches for early detection of neurocognitive disorders among older adults

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