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Alshaikh AA, Al-Qahtani FS, Taresh HMN, Hayaza RAA, Alqhtani SSM, Summan SI, Al Mansour SA, Alsultan OHA, Asiri HYM, Alqahtani YMS, Alzailaie WKA, Alamoud AAA, Ghazy RM. Prediction of Diabetes and Prediabetes among the Saudi Population Using a Non-Invasive Tool (AUSDRISK). MEDICINA (KAUNAS, LITHUANIA) 2024; 60:775. [PMID: 38792958 PMCID: PMC11123013 DOI: 10.3390/medicina60050775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 04/24/2024] [Accepted: 05/04/2024] [Indexed: 05/26/2024]
Abstract
Background and Objectives: Screening for type 2 diabetes mellitus (DM2) aims to identify asymptomatic individuals who may be at a higher risk, allowing proactive interventions. The objective of this study was to predict the incidence of DM2 and prediabetes in the Saudi population over the next five years. Materials and Methods: The study was conducted in the Aseer region through August 2023 using a cross-sectional survey for data collection. A multistage stratified random sampling technique was adopted, and data were collected through face-to-face interviews using the validated Arabic version of the Australian Type 2 Diabetes Risk Assessment Tool (AUSDRISK). Results: In total, 652 individuals were included in the study. Their mean age was 32.0 ± 12.0 years; 53.8% were male, 89.6% were from urban areas, and 55.8% were single. There were statistically significant differences between males and females in AUSDRISK items, including age, history of high blood glucose, use of medications for high blood pressure, smoking, physical activity, and measurements of waist circumference (p < 0.05). Based on AUSDRISK scores, 46.2% of the included participants were predicted to develop impaired glucose tolerance within the coming five years (65.8% among females vs. 23.6%), and 21.9% were predicted to develop DM2 (35.6% among males vs. 6.0% among females); this difference was statistically significant (p = 0.0001). Conclusions: Urgent public health action is required to prevent the increasing epidemic of DM2 in Saudi Arabia.
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Affiliation(s)
- Ayoub Ali Alshaikh
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
| | - Faisal Saeed Al-Qahtani
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
| | - Hassan Misfer N Taresh
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
| | - Rand Abdullah A Hayaza
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
| | - Sultan Saeed M Alqhtani
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
| | - Sarah Ibrahim Summan
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
| | | | - Omar Hezam A Alsultan
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
| | - Hassan Yahya M Asiri
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
| | - Yazeed Mohammed S Alqahtani
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
| | - Waleed Khaled A Alzailaie
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
| | - Ahmed Abdullah A Alamoud
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
| | - Ramy Mohamed Ghazy
- Family and Community Medicine Department, College of Medicine, King Khalid University, Abha 61423, Saudi Arabia; (A.A.A.); (F.S.A.-Q.); (H.M.N.T.); (R.A.A.H.); (S.S.M.A.); (S.I.S.); (O.H.A.A.); (H.Y.M.A.); (Y.M.S.A.)
- Tropical Health Department, High Institute of Public Health, Alexandria University, Alexandria 61421, Egypt
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Liu Y, Yu S, Feng W, Mo H, Hua Y, Zhang M, Zhu Z, Zhang X, Wu Z, Zheng L, Wu X, Shen J, Qiu W, Lou J. A meta-analysis of diabetes risk prediction models applied to prediabetes screening. Diabetes Obes Metab 2024; 26:1593-1604. [PMID: 38302734 DOI: 10.1111/dom.15457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/26/2023] [Accepted: 12/27/2023] [Indexed: 02/03/2024]
Abstract
AIM To provide a systematic overview of diabetes risk prediction models used for prediabetes screening to promote primary prevention of diabetes. METHODS The Cochrane, PubMed, Embase, Web of Science and China National Knowledge Infrastructure (CNKI) databases were searched for a comprehensive search period of 30 August 30, 2023, and studies involving diabetes prediction models for screening prediabetes risk were included in the search. The Quality Assessment Checklist for Diagnostic Studies (QUADAS-2) tool was used for risk of bias assessment and Stata and R software were used to pool model effect sizes. RESULTS A total of 29 375 articles were screened, and finally 20 models from 24 studies were included in the systematic review. The most common predictors were age, body mass index, family history of diabetes, history of hypertension, and physical activity. Regarding the indicators of model prediction performance, discrimination and calibration were only reported in 79.2% and 4.2% of studies, respectively, resulting in significant heterogeneity in model prediction results, which may be related to differences between model predictor combinations and lack of important methodological information. CONCLUSIONS Numerous models are used to predict diabetes, and as there is an association between prediabetes and diabetes, researchers have also used such models for screening the prediabetic population. Although it is a new clinical practice to explore, differences in glycaemic metabolic profiles, potential complications, and methods of intervention between the two populations cannot be ignored, and such differences have led to poor validity and accuracy of the models. Therefore, there is no recommended optimal model, and it is not recommended to use existing models for risk identification in alternative populations; future studies should focus on improving the clinical relevance and predictive performance of existing models.
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Affiliation(s)
- Yujin Liu
- Nursing Department, The second Hosiptal of Jinhua, Jinhua, China
- School of Medicine, Huzhou University, Huzhou, China
| | - Sunrui Yu
- Department of Anesthesiology, Jinhua Municipal Central Hospital, Jinhua, China
| | | | - Hangfeng Mo
- School of Medicine, Huzhou University, Huzhou, China
| | - Yuting Hua
- School of Medicine, Huzhou University, Huzhou, China
| | - Mei Zhang
- School of Medicine, Huzhou University, Huzhou, China
| | - Zhichao Zhu
- School of Medicine, Huzhou University, Huzhou, China
- Emergency Department, Jinhua Municipal Central Hospital Medical Group, Jinhua, China
| | - Xiaoping Zhang
- Nursing Department, The second Hosiptal of Jinhua, Jinhua, China
| | - Zhen Wu
- Nursing Department, The second Hosiptal of Jinhua, Jinhua, China
| | - Lanzhen Zheng
- Nursing Department, The second Hosiptal of Jinhua, Jinhua, China
| | - Xiaoqiu Wu
- Nursing Department, The second Hosiptal of Jinhua, Jinhua, China
| | - Jiantong Shen
- School of Medicine, Huzhou University, Huzhou, China
| | - Wei Qiu
- Department of Endocrinology, Huzhou Central Hospital, Huzhou, China
| | - Jianlin Lou
- Huzhou Key Laboratory of Precise Prevention and Control of Major Chronic Diseases, Huzhou University, Huzhou, China
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Nnamudi AC, Orhue NJ, Ijeh II, Nwabueze AN. Finnish diabetes risk score outperformed triglyceride-glucose index in diabetes risk prediction. J Diabetes Metab Disord 2023; 22:1337-1345. [PMID: 37975096 PMCID: PMC10638212 DOI: 10.1007/s40200-023-01252-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 06/13/2023] [Indexed: 11/19/2023]
Abstract
Purpose Triglyceride-Glucose (TyG) index is a surrogate marker of insulin resistance. This study compared the performance of TyG index and the Finnish diabetes risk score (FINDRISC) in diabetes risk prediction. Methods This cross-sectional study involved 122 young adults (aged 15-35 years) in Asaba, Delta State, Nigeria. Anthropometric measurements and biochemical analysis were done following standard protocols. Diabetes risk scoring was done using the FINDRISC questionnaire. TyG index was calculated logarithmically. Discrimination between TyG index and FINDRISC was done by plotting receiver operating characteristic (ROC) curves. Results High risk participants had significantly (p < 0.001) higher mean values of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) relative to the lower risk categories. Participants in TyG index Quartile 4 had significantly higher mean values of triglyceride (p < 0.001) and fasting plasma glucose (p < 0.05). BMI and triglyceride had the most significant (p < 0.001) positive correlation with FINDRISC and TyG index, respectively. A moderately elevated to high risk (FINDRISC ≥ 12) of developing diabetes was found in 14.8% of the participants; with a female preponderance (20.6%) relative to males (7.4%). More than half of the participants (52.5%) had slightly elevated risk and differences in diabetes risk susceptibility were significant (p < 0.001) across gender. FINDRISC had an AUC value of 0.826 while TyG index had an AUC value of 0.628 for diabetes risk prediction. Conclusion FINDRISC had a better performance than TyG index in the prediction of diabetes risk in this population. The use of other TyG-related parameters rather than TyG index is recommended in future studies. Supplementary Information The online version contains supplementary material available at 10.1007/s40200-023-01252-y.
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Affiliation(s)
- Anthony Chibuzor Nnamudi
- Department of Biochemistry, Faculty of Basic Medical Sciences, PAMO University of Medical Sciences, Port Harcourt, Nigeria
| | - Noghayin Jerry Orhue
- Department of Biochemistry, Faculty of Life Sciences, University of Benin, Benin City, Nigeria
| | - Ifeoma Irene Ijeh
- Department of Biochemistry, College of Natural and Applied Sciences, Michael Okpara University of Agriculture, Umudike, Nigeria
| | - Amarachi Nene Nwabueze
- African Centre of Excellence in Public Health and Toxicological Research (ACE-PUTOR), University of Port Harcourt, Port Harcourt, Nigeria
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Nieto-Martinez R, Barengo NC, Restrepo M, Grinspan A, Assefi A, Mechanick JI. Large scale application of the Finnish diabetes risk score in Latin American and Caribbean populations: a descriptive study. Front Endocrinol (Lausanne) 2023; 14:1188784. [PMID: 37435487 PMCID: PMC10332265 DOI: 10.3389/fendo.2023.1188784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 06/02/2023] [Indexed: 07/13/2023] Open
Abstract
Background The prevalence of type 2 diabetes (T2D) continues to increase in the Americas. Identifying people at risk for T2D is critical to the prevention of T2D complications, especially cardiovascular disease. This study gauges the ability to implement large population-based organized screening campaigns in 19 Latin American and Caribbean countries to detect people at risk for T2D using the Finnish Diabetes Risk Score (FINDRISC). Methods This cross-sectional descriptive analysis uses data collected in a sample of men and women 18 years of age or older who completed FINDRISC via eHealth during a Guinness World Record attempt campaign between October 25 and November 1, 2021. FINDRISC is a non-invasive screening tool based on age, body mass index, waist circumference, physical activity, daily intake of fruits and vegetables, history of hyperglycemia, history of antihypertensive drug treatment, and family history of T2D, assigning a score ranging from 0 to 26 points. A cut-off point of ≥ 12 points was considered as high risk for T2D. Results The final sample size consisted of 29,662 women (63%) and 17,605 men (27%). In total, 35% of subjects were at risk of T2D. The highest frequency rates (FINDRISC ≥ 12) were observed in Chile (39%), Central America (36.4%), and Peru (36.1%). Chile also had the highest proportion of people having a FINDRISC ≥15 points (25%), whereas the lowest was observed in Colombia (11.3%). Conclusions FINDRISC can be easily implemented via eHealth technology over social networks in Latin American and Caribbean populations to detect people with high risk for T2D. Primary healthcare strategies are needed to perform T2D organized screening to deliver early, accessible, culturally sensitive, and sustainable interventions to prevent sequelae of T2D, and reduce the clinical and economic burden of cardiometabolic-based chronic disease.
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Affiliation(s)
- Ramfis Nieto-Martinez
- Departments of Global Health and Population and Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, United States
- Precision Care Clinic Corp., Saint Cloud, FL, United States
- Foundation for Clinic, Public Health, Epidemiology Research of Venezuela (FISPEVEN INC), Caracas, Venezuela
| | - Noël C. Barengo
- Department of Translational Medicine, Herbert Wertheim College of Medicine & Department of Global Health, Robert Stempel College of Public Health and Social Work, Florida International University, Miami, FL, United States
- Faculty of Medicine, Riga Stradiņš University, Riga, Latvia
| | - Manuela Restrepo
- Medical Affairs Latin America, Merck Kommanditgesellschaft auf Aktien (KGaA), Darmstadt, Germany
| | - Augusto Grinspan
- Medical Affairs Latin America, Merck Kommanditgesellschaft auf Aktien (KGaA), Darmstadt, Germany
| | - Aria Assefi
- Medical Affairs Latin America, Merck Kommanditgesellschaft auf Aktien (KGaA), Darmstadt, Germany
| | - Jeffrey I. Mechanick
- The Marie-Josée and Henry R. Kravis Center for Cardiovascular Health at Mount Sinai Heart, Division of Endocrinology, Diabetes and Bone Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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Arnardóttir E, Sigurðardóttir ÁK, Graue M, Kolltveit BCH, Skinner T. Using HbA1c measurements and the Finnish Diabetes Risk Score to identify undiagnosed individuals and those at risk of diabetes in primary care. BMC Public Health 2023; 23:211. [PMID: 36721135 PMCID: PMC9887861 DOI: 10.1186/s12889-023-15122-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 01/23/2023] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Prevalence of prediabetes and type 2 diabetes mellitus (T2DM) is increasing worldwide. The objective of this study was to determine the proportion of people in Northern Iceland with prediabetes, at risk of developing T2DM or with manifest undiagnosed T2DM, as this information is lacking in Iceland. METHODS A cross-sectional study. Clients of the three largest primary health care centres in the Health Care Institution of North Iceland (HSN) were invited to participate if fulfilling the following inclusion criteria: a) aged between 18 and 75 years, b) not diagnosed with diabetes, c) speaking and understanding Icelandic or English fluently and d) living in the included service area. Data collection took place via face-to-face interviews between 1 March 2020 and 15 May 2021. Participation included answering the Finnish Diabetes Risk Score (FINDRISC), measuring the HbA1c levels and background information. RESULTS Of the 220 participants, 65.9% were women. The mean age was 52.1 years (SD ± 14.1) and FINDRISC scores were as follows: 47.3% scored ≤8 points, 37.2% scored between 9 and 14 points, and 15.5% scored between 15 and 26 points. The mean HbA1c levels in mmol/mol, were 35.5 (SD ± 3.9) for men and 34.4 (SD ± 3.4) for women, ranging from 24 to 47. Body mass index ≥30 kg/m2 was found in 32% of men and 35.9% of women. Prevalence of prediabetes in this cohort was 13.2%. None of the participants had undiagnosed T2DM. Best sensitivity and specificity for finding prediabetes was by using cut-off points of ≥11 on FINDRISC, which gave a ROC curve of 0.814. CONCLUSIONS The FINDRISC is a non-invasive and easily applied screening instrument for prediabetes. Used in advance of other more expensive and invasive testing, it can enable earlier intervention by assisting decision making, health promotion actions and prevention of the disease burden within primary health care. TRIAL REGISTRATION This study is a pre-phase of the registered study "Effectiveness of Nurse-coordinated Follow up Program in Primary Care for People at risk of T2DM" at www. CLINICALTRIALS gov (NCT01688359). Registered 30 December 2020.
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Affiliation(s)
- Elín Arnardóttir
- School of Health Sciences University of Akureyri, Akureyri, Iceland. .,Health Care Institution of North Iceland in Siglufjordur, Siglufjordur, Iceland.
| | - Árún K. Sigurðardóttir
- grid.16977.3e0000 0004 0643 4918School of Health Sciences University of Akureyri, Akureyri, Iceland ,grid.440311.30000 0004 0571 1872Akureyri Hospital, Akureyri, Iceland
| | - Marit Graue
- grid.477239.c0000 0004 1754 9964Department of Health and Caring Sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | - Beate-Christin Hope Kolltveit
- grid.477239.c0000 0004 1754 9964Department of Health and Caring Sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | - Timothy Skinner
- grid.5254.60000 0001 0674 042XInstitute of Psychology, University of Copenhagen, Copenhagen, Denmark ,Australian Centre for Behavioural Research in Diabetes, Melbourne, Victoria Australia
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Hou Y, Zhang Z, Cui Y, Peng C, Fan Y, Tan C, Wang Q, Liu Z, Gong J. Pu-erh Tea and Theabrownin Ameliorate Metabolic Syndrome in Mice via Potential Microbiota-Gut-Liver-Brain Interactions. Food Res Int 2022; 162:112176. [DOI: 10.1016/j.foodres.2022.112176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 11/03/2022] [Accepted: 11/15/2022] [Indexed: 11/21/2022]
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