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Cando LFT, Quebral EPB, Ong EP, Catral CDM, Relador RJL, Velasco AJD, Alcazar RMU, Reyes NAL, Pilotin EJB, Ornos EDB, Paz-Pacheco E, Tantengco OAG. Current status of diabetes mellitus care and management in the Philippines. Diabetes Metab Syndr 2024; 18:102951. [PMID: 38382166 DOI: 10.1016/j.dsx.2024.102951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 11/15/2023] [Accepted: 01/22/2024] [Indexed: 02/23/2024]
Abstract
AIMS In this paper, we discuss the existing data on the burden of diabetes in the Philippines and present the status of management, prevention, and control of diabetes in the country. METHODS A review of literature was conducted to synthesize the status of diabetes mellitus in the Philippines. RESULTS An estimated 4.3 million Filipinos were diagnosed with diabetes, while 2.8 million remained undiagnosed in 2021. Diabetic retinopathy is a top cause of preventable blindness in Region 3, Philippines. Diabetic nephropathy contributes to 38% of renal disease cases in the Philippines. The 2021 Philippine Guidelines on Periodic Health Examination (PhEX) advocate for the utilization of fasting blood sugar (FBS) as a screening measure for Type 2 Diabetes Mellitus (T2DM) in healthy adults aged 40 years and older or in those with specified risk factors. The alternative option of hemoglobin A1c is (HbA1c) deemed appropriate but comes with a conditional recommendation due to its uneven accessibility across different regions of the country. Treatment guidelines align between the Philippines and the US. Initial medical nutrition therapy involves healthy habits, progressing to pharmacologic treatment if necessary. Financial constraints, seen in limited insurance coverage and high out-of-pocket costs, impede care, amplifying disease impact. The complex diabetes care, encompassing pharmacotherapy, nutrition, exercise, and monitoring, faced challenges during COVID-19 quarantines. CONCLUSION In conclusion, the paper outlines diabetes care principles-screening, diagnostics, and multidisciplinary care-alongside economic implications. Local and national initiatives are discussed to mitigate diabetes trends and reduce its burden in the Philippines.
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Affiliation(s)
- Leslie Faye T Cando
- College of Medicine, University of the Philippines Manila, Manila, Philippines
| | - Elgin Paul B Quebral
- College of Medicine, University of the Philippines Manila, Manila, Philippines; Virology Laboratory, Department of Medical Microbiology, College of Public Health, University of the Philippines Manila, Manila, Philippines
| | - Erika P Ong
- College of Medicine, University of the Philippines Manila, Manila, Philippines
| | | | - Ruth Joy L Relador
- College of Medicine, University of the Philippines Manila, Manila, Philippines
| | | | | | | | - Er Joshua B Pilotin
- College of Medicine, University of the Philippines Manila, Manila, Philippines
| | - Eric David B Ornos
- Department of Medical Microbiology, College of Public Health, University of the Philippines Manila, Manila, Philippines
| | - Elizabeth Paz-Pacheco
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of the Philippines - Philippine General Hospital, Taft Avenue, Manila, Philippines
| | - Ourlad Alzeus G Tantengco
- Department of Physiology, College of Medicine, University of the Philippines Manila, Manila, Philippines; Department of Biology, College of Science, De La Salle University, Manila, Philippines.
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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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Mugume IB, Wafula ST, Kadengye DT, Van Olmen J. Performance of a Finnish Diabetes Risk Score in detecting undiagnosed diabetes among Kenyans aged 18-69 years. PLoS One 2023; 18:e0276858. [PMID: 37186010 PMCID: PMC10132597 DOI: 10.1371/journal.pone.0276858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 10/16/2022] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND The application of risk scores has often effectively predicted undiagnosed type 2 diabetes in a non-invasive way to guide early clinical management. The capacity for diagnosing diabetes in developing countries including Kenya is limited. Screening tools to identify those at risk and thus target the use of limited resources could be helpful, but these are not validated for use in these settings. We, therefore, aimed to measure the performance of the Finnish diabetes risk score (FINDRISC) as a screening tool to detect undiagnosed diabetes among Kenyan adults. METHODS A nationwide cross-sectional survey on non-communicable disease risk factors was conducted among Kenyan adults between April and June 2015. Diabetes mellitus was defined as fasting capillary whole blood ≥ 7.0mmol/l. The performance of the original, modified, and simplified FINDRISC tools in predicting undiagnosed diabetes was assessed using the area under the receiver operating curve (AU-ROC). Non-parametric analyses of the AU-ROC, Sensitivity (Se), and Specificity (Sp) of FINDRISC tools were determined. RESULTS A total of 4,027 data observations of individuals aged 18-69 years were analyzed. The proportion/prevalence of undiagnosed diabetes and prediabetes was 1.8% [1.3-2.6], and 2.6% [1.9-3.4] respectively. The AU-ROC of the modified FINDRISC and simplified FINDRISC in detecting undiagnosed diabetes were 0.7481 and 0.7486 respectively, with no statistically significant difference (p = 0.912). With an optimal cut-off ≥ 7, the simplified FINDRISC had a higher positive predictive value (PPV) (7.9%) and diagnostic odds (OR:6.65, 95%CI: 4.43-9.96) of detecting undiagnosed diabetes than the modified FINDRISC. CONCLUSION The simple, non-invasive modified, and simplified FINDRISC tools performed well in detecting undiagnosed diabetes and may be useful in the Kenyan population and other similar population settings. For resource-constrained settings like the Kenyan settings, the simplified FINDRISC is preferred.
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Affiliation(s)
- Innocent B Mugume
- Department of Integrated Epidemiology, Surveillance and Public Health Emergencies, Ministry of Health, Kampala, Uganda
- Department of Epidemiology and Social Medicine, Faculty of Medicine and Health Sciences University of Antwerp, Antwerp, Belgium
| | - Solomon T Wafula
- Department of Disease Control and Environmental Health, School of Public Health, Uganda Makerere University, Kampala, Uganda
| | | | - Josefien Van Olmen
- Department of Family Medicine and Population Health, Global Health Institute, University of Antwerp, Antwerp, Belgium
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Rokhman MR, Arifin B, Zulkarnain Z, Satibi S, Perwitasari DA, Boersma C, Postma MJ, van der Schans J. Translation and performance of the Finnish Diabetes Risk Score for detecting undiagnosed diabetes and dysglycaemia in the Indonesian population. PLoS One 2022; 17:e0269853. [PMID: 35862370 PMCID: PMC9302803 DOI: 10.1371/journal.pone.0269853] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 05/29/2022] [Indexed: 12/15/2022] Open
Abstract
A diabetes risk score cannot directly be translated and applied in different populations, and its performance should be evaluated in the target population. This study aimed to translate the Finnish Diabetes Risk Score (FINDRISC) instrument and compare its performance with the modified version for detecting undiagnosed type 2 diabetes mellitus (T2DM) and dysglycaemia among the Indonesian adult population. Forward and backward translations were performed and followed by cultural adaptation. In total, 1,403 participants were recruited. The FINDRISC-Bahasa Indonesia (FINDRISC-BI) was scored according to the original FINDRISC instrument, while a Modified FINDRISC-BI was analyzed using a specific body mass index and waist circumference classification for Indonesians. The area under the receiver operating characteristic curve, sensitivity, specificity, and the optimal cut-offs of both instruments were estimated. The area under the receiver operating characteristic curve for detecting undiagnosed T2DM was 0.73 (0.67–0.78) for the FINDRISC-BI with an optimal cut-off score of ≥9 (sensitivity = 63.0%; specificity = 67.3%) and 0.72 (0.67–0.78) for the Modified FINDRISC-BI with an optimal cut-off score of ≥11 (sensitivity = 59.8%; specificity = 74.9%). The area under the receiver operating characteristic curve for detecting dysglycaemia was 0.72 (0.69–0.75) for the FINDRISC-BI instrument with an optimal cut-off score of ≥8 (sensitivity = 66.4%; specificity = 67.0%), and 0.72 (0.69–0.75) for the Modified FINDRISC-BI instrument with an optimal cut-off score ≥9 (sensitivity = 63.8%; specificity = 67.6%). The Indonesian version of the FINDRISC instrument has acceptable diagnostic accuracy for screening people with undiagnosed T2DM or dysglycaemia in Indonesia. Modifying the body mass index and waist circumference classifications in the Modified FINDRISC-BI results in a similar diagnostic accuracy; however, the Modified FINDRISC-BI has a higher optimal cut-off point than the FINDRISC-BI. People with an above optimal cut-off score are suggested to take a further blood glucose test.
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Affiliation(s)
- M. Rifqi Rokhman
- Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Institute of Science in Healthy Ageing & healthcaRE (SHARE), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia
- * E-mail: , (MRR); , (BA)
| | - Bustanul Arifin
- Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Faculty of Pharmacy, Universitas Hasanuddin, Makassar, Indonesia
- Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
- Unit of PharmacoTherapy, Epidemiology and Economics (PTE2), Department of Pharmacy, University of Groningen, Groningen, The Netherlands
- * E-mail: , (MRR); , (BA)
| | - Zulkarnain Zulkarnain
- Faculty of Medicine, Universitas Syiah Kuala, Banda Aceh, Indonesia
- Thyroid Center, Zainoel Abidin Hospital, Banda Aceh, Indonesia
| | - Satibi Satibi
- Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | | | - Cornelis Boersma
- Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Institute of Science in Healthy Ageing & healthcaRE (SHARE), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Faculty of Management Sciences, Open University, Heerlen, The Netherlands
| | - Maarten J. Postma
- Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Institute of Science in Healthy Ageing & healthcaRE (SHARE), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Unit of PharmacoTherapy, Epidemiology and Economics (PTE2), Department of Pharmacy, University of Groningen, Groningen, The Netherlands
- Department of Pharmacology and Therapy, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia
- Department of Economics, Econometrics and Finance, Faculty of Economics & Business, University of Groningen, Groningen, The Netherlands
| | - Jurjen van der Schans
- Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Institute of Science in Healthy Ageing & healthcaRE (SHARE), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Economics, Econometrics and Finance, Faculty of Economics & Business, University of Groningen, Groningen, The Netherlands
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Jin S, Chen Q, Han X, Liu Y, Cai M, Yao Z, Lu H. Comparison of the Finnish Diabetes Risk Score Model With the Metabolic Syndrome in a Shanghai Population. Front Endocrinol (Lausanne) 2022; 13:725314. [PMID: 35273562 PMCID: PMC8902815 DOI: 10.3389/fendo.2022.725314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 01/27/2022] [Indexed: 11/13/2022] Open
Abstract
AIMS This study aimed to compare the diagnostic accuracy of the metabolic syndrome with the Finnish Diabetes Risk Score (FINDRISC) to screen for type 2 diabetes mellitus (T2DM) in a Shanghai population. METHODS Participants aged 25-64 years were recruited from a Shanghai population from July 2019 to March 2020. Each participant underwent a standard metabolic work-up, including clinical examination with anthropometry. Glucose status was tested using hemoglobin A1c (HbAlc), 2h-post-load glucose (2hPG), and fasting blood glucose (FBG). The FINDRISC questionnaire and the metabolic syndrome were examined. The performance of the FINDRISC was assessed using the area under the receiver operating characteristic curve (AUC-ROC). RESULTS Of the 713 subjects, 9.1% were diagnosed with prediabetes, whereas 5.2% were diagnosed with T2DM. A total of 172 subjects had the metabolic syndrome. A higher FINDRISC score was positively associated with the prevalence of T2DM and the metabolic syndrome. Multivariable linear regression analysis demonstrated that the FINDRISC had a linear regression relationship with 2hPG levels (b'= 036, p < 0.0001). The AUC-ROC of the FINDRISC to identify subjects with T2DM among the total population was 0.708 (95% CI 0.639-0.776), the sensitivity was 44.6%, and the specificity was 90.1%, with 11 as the cut-off point. After adding FBG or 2hPG to the FINDRISC, the AUC-ROC among the total population significantly increased to 0.785 (95% CI 0.671-0.899) and 0.731 (95% CI 0.619-0.843), respectively, while the AUC-ROC among the female group increased to 0.858 (95% CI 0.753-0.964) and 0.823 (95% CI 0.730-0.916), respectively (p < 0.001). The AUC-ROC of the metabolic syndrome to identify subjects with T2DM among the total and female population was 0.805 (95% CI 0.767-0.844) and 0.830 (95% CI 0.788-0.872), respectively, with seven as the cut-off point. CONCLUSIONS The metabolic syndrome performed better than the FINDRISC model. The metabolic syndrome and the FINDRISC with FBG or 2hPG in a two-step screening model are both efficacious clinical practices for predicting T2DM in a Shanghai population.
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Affiliation(s)
| | | | | | | | | | - Zheng Yao
- *Correspondence: Zheng Yao, ; Hao Lu,
| | - Hao Lu
- *Correspondence: Zheng Yao, ; Hao Lu,
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Gračner T. Bittersweet: How prices of sugar-rich foods contribute to the diet-related disease epidemic in Mexico. JOURNAL OF HEALTH ECONOMICS 2021; 80:102506. [PMID: 34537582 DOI: 10.1016/j.jhealeco.2021.102506] [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: 06/11/2020] [Revised: 04/30/2021] [Accepted: 07/13/2021] [Indexed: 06/13/2023]
Abstract
I provide new evidence on how price changes of nutritionally similar foods, such as those rich in sugar or fats, change obesity and diet-related diseases in the context of Mexico between 1996-2010. I merge a bar-code level price dataset with product-specific nutritional composition to two datasets with health outcomes: state-level administrative and nationally representative individual-level panel data. Exploiting within-city variation in prices using fixed effects models, I show that decreased prices of sugar-rich foods increase obesity, type 2 diabetes, and hypertension prevalence; yet the prices of foods rich in other nutrients do not. Health responses to price changes are the largest for those abdominally obese or at the highest risk for chronic disease. The association between prices of sugary foods and chronic disease is meaningful: I estimate that in Mexico, price reductions of sugary foods explain roughly 15 percent of the rise in obesity and diabetes during the 15-year study period.
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Affiliation(s)
- Tadeja Gračner
- RAND Corporation, 1776 Main St, Santa Monica, CA 90401, United States.
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Ydirin CSB. Health literacy and health-promoting behaviors among adults at risk for diabetes in a remote Filipino community. BELITUNG NURSING JOURNAL 2021; 7:88-97. [PMID: 37469942 PMCID: PMC10353656 DOI: 10.33546/bnj.1298] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 02/17/2021] [Accepted: 03/01/2021] [Indexed: 07/21/2023] Open
Abstract
Background Diabetes risk assessment is an essential preboarding tool before implementing health literacy programs to change an adult's health behavior positively. Research has shown an association between health literacy and health behaviors, but there is a dearth of literature that delineates the difference between the health literacy and health behaviors of adults according to their diabetes risks; high risk vs. low risk. Objective This study aimed to determine the difference between the health literacy and health behaviors of adults and establish the relationship between the two variables when classified according to their diabetes risks. Methods This study utilized a descriptive cross-sectional design with 400 adults in a remote Filipino community in November 2019. Data were gathered using the Health Promoting Lifestyle Profile II (HPLP II) and Health Literacy Survey-Short Form 12 (HLS-SF12) questionnaires. Descriptive statistics, independent t-test, and Pearson's r were used to analyze the data. Results There is a significant difference between the health literacy index scores (p < .05); but no significant difference between the health behavior mean scores (p > .05) of adults when grouped according to their diabetes risks. Health literacy is significantly (p < .05) correlated with health behaviors of adults, with a moderate positive correlation in the high-risk group (r = .43), and both weak positive correlation in the low-risk group (r = .13) and entire group (r = .17). Conclusion All adult inclusion efforts in promoting health literacy, with emphasis on the high-risk group, are needed to improve awareness of the degree of diabetes risks. Nurses should take an active role in the assessment of diabetes risks, evaluation of results, and implementation of interventions that could increase health literacy to facilitate the development of healthy behaviors. Stakeholders are urged to advance the availability of evidence-based lifestyle interventions to reduce the growth in new cases of diabetes.
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Lim HM, Chia YC, Koay ZL. Performance of the Finnish Diabetes Risk Score (FINDRISC) and Modified Asian FINDRISC (ModAsian FINDRISC) for screening of undiagnosed type 2 diabetes mellitus and dysglycaemia in primary care. Prim Care Diabetes 2020; 14:494-500. [PMID: 32156516 DOI: 10.1016/j.pcd.2020.02.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 02/14/2020] [Accepted: 02/25/2020] [Indexed: 12/18/2022]
Abstract
AIMS To evaluate the performance of FINDRISC and ModAsian FINDRISC for the screening of undiagnosed diabetes and dysglycaemia in primary care. To compare the performance of FINDRISC with the recommendations of the American Diabetes Association (ADA) and US Preventive Services Task Force (USPSTF) guidelines. METHODS This cross-sectional study was carried out on 293 patients without a prior history of diabetes at a primary care clinic in Malaysia. Questions on body mass index and waist circumference were modified based on the Asian standard in ModAsian FINDRISC. Haemoglobin A1c of ≥6.5% (48 mmol/mol) was used to diagnose diabetes. Areas under the receiver operating curve (ROC-AUC) for FINDRISC and ModAsian FINDRISC were analyzed. RESULTS The prevalence of undiagnosed diabetes was 7.5% and prediabetes was 32.8%. The ROC-AUC of FINDRISC was 0.76 (undiagnosed diabetes) and 0.79 (dysglycaemia). There was no statistical difference between FINDRISC and ModAsian FINDRISC. The recommended optimal FINDRISC cut-off point for undiagnosed diabetes was ≥11 (Sensitivity 86.4%, Specificity 48.7%). FINDRISC ≥11 point has higher sensitivity compared to USPSTF criteria (72.7%) and higher specificity compared to the ADA (9.6%). CONCLUSIONS FINDRISC is a useful diabetes screening tool to identify those at risk of diabetes in primary care in Malaysia.
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Affiliation(s)
- Hooi Min Lim
- Department of Primary Care Medicine, University Malaya Medical Centre, University of Malaya, Kuala Lumpur, Malaysia.
| | - Yook Chin Chia
- Department of Primary Care Medicine, University Malaya Medical Centre, University of Malaya, Kuala Lumpur, Malaysia; Department of Medical Sciences, School of Healthcare and Medical Sciences, Sunway University, Selangor, Malaysia.
| | - Zhong Lin Koay
- Department of Primary Care Medicine, University Malaya Medical Centre, University of Malaya, Kuala Lumpur, Malaysia.
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Agreement between Type 2 Diabetes Risk Scales in a Caucasian Population: A Systematic Review and Report. J Clin Med 2020; 9:jcm9051546. [PMID: 32443837 PMCID: PMC7290893 DOI: 10.3390/jcm9051546] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 05/05/2020] [Accepted: 05/18/2020] [Indexed: 02/07/2023] Open
Abstract
Early detection of people with undiagnosed type 2 diabetes (T2D) is an important public health concern. Several predictive equations for T2D have been proposed but most of them have not been externally validated and their performance could be compromised when clinical data is used. Clinical practice guidelines increasingly incorporate T2D risk prediction models as they support clinical decision making. The aims of this study were to systematically review prediction scores for T2D and to analyze the agreement between these risk scores in a large cross-sectional study of white western European workers. A systematic review of the PubMed, CINAHL, and EMBASE databases and a cross-sectional study in 59,042 Spanish workers was performed. Agreement between scores classifying participants as high risk was evaluated using the kappa statistic. The systematic review of 26 predictive models highlights a great heterogeneity in the risk predictors; there is a poor level of reporting, and most of them have not been externally validated. Regarding the agreement between risk scores, the DETECT-2 risk score scale classified 14.1% of subjects as high-risk, FINDRISC score 20.8%, Cambridge score 19.8%, the AUSDRISK score 26.4%, the EGAD study 30.3%, the Hisayama study 30.9%, the ARIC score 6.3%, and the ITD score 3.1%. The lowest agreement was observed between the ITD and the NUDS study derived score (κ = 0.067). Differences in diabetes incidence, prevalence, and weight of risk factors seem to account for the agreement differences between scores. A better agreement between the multi-ethnic derivate score (DETECT-2) and European derivate scores was observed. Risk models should be designed using more easily identifiable and reproducible health data in clinical practice.
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Abdallah M, Sharbaji S, Sharbaji M, Daher Z, Faour T, Mansour Z, Hneino M. Diagnostic accuracy of the Finnish Diabetes Risk Score for the prediction of undiagnosed type 2 diabetes, prediabetes, and metabolic syndrome in the Lebanese University. Diabetol Metab Syndr 2020; 12:84. [PMID: 33014142 PMCID: PMC7526372 DOI: 10.1186/s13098-020-00590-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Accepted: 09/19/2020] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Risk scores were mainly proved to predict undiagnosed type 2 diabetes mellitus (UT2DM) in a non-invasive manner and to guide earlier clinical treatment. The objective of the present study was to assess the performance of the Finnish Diabetes Risk Score (FINDRISC) for detecting three outcomes: UT2DM, prediabetes, and the metabolic syndrome (MS). METHODS This was a prospective, cross-sectional study during which employees aged between 30 and 64, with no known diabetes and working within the faculties of the Lebanese University (LU) were conveniently recruited. Participants completed the FINDRISC questionnaire and their glucose levels were examined using both fasting blood glucose (FBG) and oral glucose tolerance tests (OGTT). Furthermore, they underwent lipid profile tests with anthropometry. RESULTS Of 713 subjects, 397 subjects (55.2% female; 44.8% male) completed the blood tests and thus were considered as the sample population. 7.6% had UT2DM, 22.9% prediabetes and 35.8% had MS, where men had higher prevalence than women for these 3 outcomes (P = 0.001, P = 0.003 and P = 0.001) respectively. The AUROC value with 95% Confidence Interval (CI) for detecting UT2DM was 0.795 (0.822 in men and 0.725 in women), 0.621(0.648 in men and 0.59 in women) for prediabetes and 0.710 (0.734 in men and 0.705 in women) for MS. The correspondent optimal cut-off point for UT2DM was 11.5 (sensitivity = 83.3% and specificity = 61.3%), 9.5 for prediabetes (sensitivity = 73.6% and specificity = 43.1%) and 10.5 (sensitivity = 69.7%; specificity = 56.5%) for MS. CONCLUSION The FINDRISC can be considered a simple, quick, inexpensive, and non-invasive instrument to use in a Lebanese community of working people who are unaware of their health status and who usually report being extremely busy because of their daily hectic work for the screening of UT2DM and MS. However, it poorly screens for prediabetes in this context.
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Affiliation(s)
- Maher Abdallah
- Faculty of Public Health, Lebanese University, Hadat, Beirut, Lebanon
| | - Safa Sharbaji
- Department of Nutrition and Dietetics, Faculty of Public Health, Lebanese University, Hadat, Beirut, Lebanon
| | - Marwa Sharbaji
- Department of Nutrition and Dietetics, Faculty of Public Health, Lebanese University, Hadat, Beirut, Lebanon
| | - Zeina Daher
- Faculty of Public Health, Lebanese University, Hadat, Beirut, Lebanon
| | - Tarek Faour
- Medical Laboratory, Lebanese University Medical Center, Lebanese University, Hadat, Beirut, Lebanon
| | - Zeinab Mansour
- Medical Laboratory, Lebanese University Medical Center, Lebanese University, Hadat, Beirut, Lebanon
| | - Mohammad Hneino
- Sciences Department, Faculty of Public Health, Lebanese University Hadat, Hadat, Beirut, Lebanon
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Agarwal G, Guingona MM, Gaber J, Angeles R, Rao S, Cristobal F. Choosing the most appropriate existing type 2 diabetes risk assessment tool for use in the Philippines: a case-control study with an urban Filipino population. BMC Public Health 2019; 19:1169. [PMID: 31455247 PMCID: PMC6712874 DOI: 10.1186/s12889-019-7402-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 07/30/2019] [Indexed: 11/12/2022] Open
Abstract
Background As the prevalence of type 2 diabetes (T2DM) increases in low- to middle-income countries, the burden on individuals and health care systems also increases. The use of diabetes risk assessment tools could identify those at risk, leading to prevention or early detection of diabetes. The aim of this study was to evaluate the appropriateness of 6 existing T2DM risk screening tools in detecting dysglycemia in Zamboanga City, Philippines. Methods This study used a case-control design in an urban setting in the southern Philippines. There were 200 participants in two groups: 1) those diagnosed with diabetes (n = 50; recruited from diabetes clinics) and 2) those with no previous diagnosis of diabetes (n = 150; recruited from community locations). Participants completed six tools (the Finnish Diabetes Risk Score [FINDRISC], the Canadian Diabetes Risk Score [CANRISK], the Indian Diabetes Risk Score [IDRS], the American Diabetes Association [ADA] risk score, an Indonesian undiagnosed diabetes mellitus [UDDM] scoring system, and a Filipino tool). Scores were compared to fasting plasma glucose levels, which are recommended in Philippines clinical practice guidelines as a valid, available, and low cost option for T2DM diagnosis. Appropriateness of tools was determined through accuracy, sensitivity, specificity, positive/negative predictive value (PPV, NPV), and positive/negative likelihood ratios. Results The Filipino tool had the highest specificity (0.73) and PPV (0.27), but lowest sensitivity (0.68). The IDRS and Indonesian UDDM tool had the highest NPV at 0.96, but were not amongst the highest in other scores. The CANRISK tied for highest area under the receiver operating characteristic (ROC) curve (AUC), AUC (0.80), but other scores were not noteworthy. Overall, the FINDRISC was the most effective with highest sensitivity (0.94), tied for highest AUC (0.80), and with middle scores in other variables (specificity: 0.45, PPV: 0.20, NPV: 0.95), when using the published cut-off score of 9. When increasing the cut-off score to 11, specificity increased (0.71) and sensitivity was not greatly affected (0.86). Conclusions Our results suggest that the FINDRISC is more suitable than other known diabetes risk assessment tools in an urban Filipino population; effectiveness increased with a higher cut-off score. Electronic supplementary material The online version of this article (10.1186/s12889-019-7402-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Gina Agarwal
- Department of Family Medicine, McMaster University, 1280 Main Street West, David Braley Health Sciences Centre 3rd Floor, Hamilton, Ontario, L8S 4K1, Canada.
| | | | - Jessica Gaber
- Department of Family Medicine, McMaster University, 1280 Main Street West, David Braley Health Sciences Centre 3rd Floor, Hamilton, Ontario, L8S 4K1, Canada
| | - Ricardo Angeles
- Department of Family Medicine, McMaster University, 1280 Main Street West, David Braley Health Sciences Centre 3rd Floor, Hamilton, Ontario, L8S 4K1, Canada
| | - Suhasini Rao
- Department of Family Medicine, McMaster University, 1280 Main Street West, David Braley Health Sciences Centre 3rd Floor, Hamilton, Ontario, L8S 4K1, Canada
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Agarwal G, Angeles RN, Dolovich L, Kaczorowski J, Gaber J, Guenter D, Arnuco FD, Lam HY, Thabane L, O'Reilly D, Agbulos RM, Arciaga RS, Barrera J, Gregorio E, Halili S, Jalani N, Cristobal F. The Community Health Assessment Program in the Philippines (CHAP-P) diabetes health promotion program for low- to middle-income countries: study protocol for a cluster randomized controlled trial. BMC Public Health 2019; 19:682. [PMID: 31159778 PMCID: PMC6547510 DOI: 10.1186/s12889-019-6974-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Accepted: 05/14/2019] [Indexed: 11/17/2022] Open
Abstract
Background Type 2 diabetes is increasing globally, with the highest burden in low- to middle-income countries (LMICs) such as the Philippines. Developing effective interventions could improve detection, prevention, and treatment of diabetes. The Cardiovascular Health Awareness Program (CHAP), an evidence-based Canadian intervention, may be an appropriate model for LMICs due to its low cost, ease of implementation, and focus on health promotion and disease prevention. The primary aim of this study is to adapt the CHAP model to a Philippine context as the Community Health Assessment Program in the Philippines (CHAP-P) and evaluate the effect of CHAP-P on glycated hemoglobin (HbA1c) compared to a random sample of community residents in control communities. Methods Six-month, 26-community (13 intervention, 13 control) parallel cluster randomized controlled trial in Zamboanga Peninsula, an Administrative Region in the southern Philippines. Criteria for community selection include: adequate political stability, connection with local champions, travel feasibility, and refrigerated space for materials. The community-based intervention, CHAP-P sessions, are volunteer-led group sessions with chronic condition assessment, blood pressure monitoring, and health education. Three participant groups will be involved: 1) Random sample of community participants aged 40 or older, 100 per community (1300 control, 1300 intervention participants total); 2) Community members aged 40 years or older who attended at least one CHAP-P session; 3) Community health workers and staff facilitating sessions. Primary outcome: mean difference in HbA1c at 6 months in intervention group individuals compared to control. Secondary outcomes: modifiable risk factors, health utilization and access (individual); diabetes detection and management (cluster). Evaluation also includes community process evaluation and cost-effectiveness analysis. Discussion CHAP has been shown to be effective in a Canadian setting. Individual components of CHAP-P have been piloted locally and shown to be acceptable and feasible. This study will improve understanding of how best to adapt this model to an LMIC setting, in order to maximize prevention, detection, and management of diabetes. Results may inform policy and practice in the Philippines and have the potential to be applied to other LMICs. Trial registration ClinicalTrials.gov (NCT03481335), registered March 29, 2018. Electronic supplementary material The online version of this article (10.1186/s12889-019-6974-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Gina Agarwal
- Department of Family Medicine, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4L8, Canada.
| | - Ricardo N Angeles
- Department of Family Medicine, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4L8, Canada.,School of Medicine, Ateneo de Zamboanga University, La Purisima St, 7000, Zamboanga City, Philippines
| | - Lisa Dolovich
- Department of Family Medicine, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4L8, Canada.,Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario, M5S 3M2, Canada
| | - Janusz Kaczorowski
- Department of Family and Emergency Medicine, University of Montreal and CRCHUM, 850 Saint-Denis St, Montreal, Quebec, H2X 0A9, Canada
| | - Jessica Gaber
- Department of Family Medicine, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4L8, Canada
| | - Dale Guenter
- Department of Family Medicine, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4L8, Canada
| | - Floro Dave Arnuco
- School of Medicine, Ateneo de Zamboanga University, La Purisima St, 7000, Zamboanga City, Philippines
| | - Hilton Y Lam
- Institute of Health Policy and Development Studies, University of the Philippines Manila, One Adriatico Place Tower One, Adriatico Street Corner Pedro Gill Street, 1000, Manila, Philippines
| | - Lehana Thabane
- Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4L8, Canada
| | - Daria O'Reilly
- Department of Health Research Methods, Evidence, and Impact, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4L8, Canada
| | - Rodelin M Agbulos
- Zamboanga City Health Office, Pettit Barracks, 7000, Zamboanga City, Philippines
| | - Rosemarie S Arciaga
- School of Medicine, Ateneo de Zamboanga University, La Purisima St, 7000, Zamboanga City, Philippines.,Zamboanga Medical Research Foundation, Zamboanga City, Philippines
| | - Jerome Barrera
- School of Medicine, Ateneo de Zamboanga University, La Purisima St, 7000, Zamboanga City, Philippines
| | - Elgie Gregorio
- School of Medicine, Ateneo de Zamboanga University, La Purisima St, 7000, Zamboanga City, Philippines
| | - Servando Halili
- Graduate School, Ateneo de Zamboanga University, La Purisima St, 7000, Zamboanga City, Philippines
| | - Norvie Jalani
- Department of Health, Zamboanga Peninsula, 7000, Zamboanga City, Philippines
| | - Fortunato Cristobal
- School of Medicine, Ateneo de Zamboanga University, La Purisima St, 7000, Zamboanga City, Philippines
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Mavrogianni C, Lambrinou CP, Androutsos O, Lindström J, Kivelä J, Cardon G, Huys N, Tsochev K, Iotova V, Chakarova N, Rurik I, Moreno LA, Liatis S, Makrilakis K, Manios Y. Evaluation of the Finnish Diabetes Risk Score as a screening tool for undiagnosed type 2 diabetes and dysglycaemia among early middle-aged adults in a large-scale European cohort. The Feel4Diabetes-study. Diabetes Res Clin Pract 2019; 150:99-110. [PMID: 30796939 DOI: 10.1016/j.diabres.2019.02.017] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Revised: 01/31/2019] [Accepted: 02/18/2019] [Indexed: 12/13/2022]
Abstract
AIM To assess the diagnostic accuracy of the FINDRISC for undiagnosed type 2 diabetes mellitus (T2DM) and dysglycaemia (i.e. the presence of prediabetes or T2DM) among early middle-aged adults from vulnerable groups in a large-scale European cohort. METHODS Participants were recruited from low-socioeconomic areas in high-income countries (HICs) (Belgium-Finland) and in HICs under austerity measures (Greece-Spain) and from the overall population in low/middle-income countries (LMICs) (Bulgaria-Hungary). Study population comprised of 2116 parents of primary-school children from families identified at increased risk of T2DM, based on parental self-reported FINDRISC. Sensitivity (Se), specificity (Sp), area under the receiver operating characteristic curves (AUC-ROC) and the optimal cut-offs of FINDRISC that indicate an increased probability for undiagnosed T2DM or dysglycaemia were calculated. RESULTS The AUC-ROC for undiagnosed T2DM was 0.824 with optimal cut-off ≥14 (Se = 68%, Sp = 81.7%) for the total sample, 0.839 with optimal cut-off ≥15 (Se = 83.3%, Sp = 86.9%) for HICs, 0.794 with optimal cut-off ≥12 (Se = 83.3%, Sp = 61.1%) for HICs under austerity measures and 0.882 with optimal cut-off ≥14 (Se = 71.4%, Sp = 87.8%) for LMICs. The AUC-ROC for dysglycaemia was 0.663 with optimal cut-off ≥12 (Se = 58.3%, Sp = 65.7%) for the total sample, 0.656 with optimal cut-off ≥12 (Se = 54.5%, Sp = 64.8%) for HICs, 0.631 with optimal cut-off ≥12 (Se = 59.7%, Sp = 62.0%) for HICs under austerity measures and 0.735 with optimal cut-off ≥11 (Se = 72.7%, Sp = 70.2%) for LMICs. CONCLUSION FINDRISC can be applied for screening primarily undiagnosed T2DM but also dysglycaemia among vulnerable groups across Europe, considering the use of different cut-offs for each subpopulation.
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Affiliation(s)
- Christina Mavrogianni
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Christina-Paulina Lambrinou
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Odysseas Androutsos
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Jaana Lindström
- National Institute for Health and Welfare, Helsinki, Finland
| | - Jemina Kivelä
- National Institute for Health and Welfare, Helsinki, Finland
| | - Greet Cardon
- Department of Movement and Sport Sciences, Ghent University, Ghent, Belgium
| | - Nele Huys
- Department of Movement and Sport Sciences, Ghent University, Ghent, Belgium
| | - Kaloyan Tsochev
- Department of Pediatrics, Medical University Varna, Varna, Bulgaria
| | - Violeta Iotova
- Department of Pediatrics, Medical University Varna, Varna, Bulgaria
| | - Nevena Chakarova
- Department of Diabetology, Clinical Center of Endocrinology, Medical University Sofia, Sofia, Bulgaria
| | - Imre Rurik
- Department of Family and Occupational Medicine, University of Debrecen, Debrecen, Hungary
| | - Luis A Moreno
- GENUD (Growth, Exercise, Nutrition and Development) Research Group, University of Zaragoza, Zaragoza, Spain
| | - Stavros Liatis
- First Department of Propaedeutic Internal Medicine, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Konstantinos Makrilakis
- First Department of Propaedeutic Internal Medicine, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Yannis Manios
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece.
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14
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Skolbekken JA. Online risk numbers – helpful, meaningless or simply wrong? Reflections on online risk calculators. Health (London) 2019; 23:401-417. [DOI: 10.1177/1363459319826183] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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15
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Leung AY, Xu XY, Chau PH, Yu YTE, Cheung MK, Wong CK, Fong DY, Wong JY, Lam CL. A Mobile App for Identifying Individuals With Undiagnosed Diabetes and Prediabetes and for Promoting Behavior Change: 2-Year Prospective Study. JMIR Mhealth Uhealth 2018; 6:e10662. [PMID: 29793901 PMCID: PMC5992453 DOI: 10.2196/10662] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Revised: 05/07/2018] [Accepted: 05/08/2018] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND To decrease the burden of diabetes in society, early screening of undiagnosed diabetes and prediabetes is needed. Integrating a diabetes risk score into a mobile app would provide a useful platform to enable people to self-assess their risk of diabetes with ease. OBJECTIVE The objectives of this study were to (1) assess the profile of Diabetes Risk Score mobile app users, (2) determine the optimal cutoff value of the Finnish Diabetes Risk Score to identify undiagnosed diabetes and prediabetes in the Chinese population, (3) estimate users' chance of developing diabetes within 2 years of using the app, and (4) investigate high-risk app users' lifestyle behavior changes after ascertaining their risk level from the app. METHODS We conducted this 2-phase study among adults via mobile app and online survey from August 2014 to December 2016. Phase 1 adopted a cross-sectional design, with a descriptive analysis of the app users' profile. We used a Cohen kappa score to show the agreement between the risk level (as shown in the app) and glycated hemoglobin test results. We used sensitivity, specificity, and area under the curve to determine the optimal cutoff value of the diabetes risk score in this population. Phase 2 was a prospective cohort study. We used a logistic regression model to estimate the chance of developing diabetes after using the app. Paired t tests compared high-risk app users' lifestyle changes. RESULTS A total of 13,289 people used the app in phase 1a. After data cleaning, we considered 4549 of these as valid data. Most users were male, and 1811 (39.81%) had tertiary education or above. Among them, 188 (10.4%) users agreed to attend the health assessment in phase 1b. We recommend the optimal value of the diabetes risk score for identifying persons with undiagnosed diabetes and prediabetes to be 9, with an area under the receiver operating characteristic curve of 0.67 (95% CI 0.60-0.74), sensitivity of 0.70 (95% CI 0.58-0.80), and specificity of 0.57 (95% CI 0.47-0.66). At the 2-year follow-up, people in the high-risk group had a higher chance of developing diabetes (odds ratio 4.59, P=.048) than the low-risk group. The high-risk app users improved their daily intake of vegetables (baseline: mean 0.76, SD 0.43; follow-up: mean 0.93, SD 0.26; t81=-3.77, P<.001) and daily exercise (baseline: mean 0.40, SD 0.49; follow-up: mean 0.54, SD 0.50; t81=-2.08, P=.04). CONCLUSIONS The Diabetes Risk Score app has been shown to be a feasible and reliable tool to identify persons with undiagnosed diabetes and prediabetes and to predict diabetes incidence in 2 years. The app can also encourage high-risk people to modify dietary habits and reduce sedentary lifestyle.
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Affiliation(s)
- Angela Ym Leung
- Centre for Gerontological Nursing, School of Nursing, The Hong Kong Polytechnic University, Hong Kong SAR, China (Hong Kong)
| | - Xin Yi Xu
- Centre for Gerontological Nursing, School of Nursing, The Hong Kong Polytechnic University, Hong Kong SAR, China (Hong Kong)
| | - Pui Hing Chau
- School of Nursing, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Yee Tak Esther Yu
- Department of Family Medicine and Primary Care, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Mike Kt Cheung
- Centre on Research and Advocacy, The Hong Kong Society for Rehabilitation, Hong Kong, China (Hong Kong)
| | - Carlos Kh Wong
- Department of Family Medicine and Primary Care, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Daniel Yt Fong
- School of Nursing, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Janet Yh Wong
- School of Nursing, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Cindy Lk Lam
- Department of Family Medicine and Primary Care, The University of Hong Kong, Hong Kong, China (Hong Kong)
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Štiglic G, Kocbek P, Cilar L, Fijačko N, Stožer A, Zaletel J, Sheikh A, Povalej Bržan P. Development of a screening tool using electronic health records for undiagnosed Type 2 diabetes mellitus and impaired fasting glucose detection in the Slovenian population. Diabet Med 2018; 35:640-649. [PMID: 29460977 DOI: 10.1111/dme.13605] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/15/2018] [Indexed: 12/14/2022]
Abstract
AIM To develop and validate a simplified screening test for undiagnosed Type 2 diabetes mellitus and impaired fasting glucose for the Slovenian population (SloRisk) to be used in the general population. METHODS Data on 11 391 people were collected from the electronic health records of comprehensive medical examinations in five Slovenian healthcare centres. Fasting plasma glucose as well as information related to the Finnish Diabetes Risk Score questionnaire, FINDRISC, were collected for 2073 people to build predictive models. Bootstrapping-based evaluation was used to estimate the area under the receiver-operating characteristic curve performance metric of two proposed logistic regression models as well as the Finnish Diabetes Risk Score model both at recommended and at alternative cut-off values. RESULTS The final model contained five questions for undiagnosed Type 2 diabetes prediction and achieved an area under the receiver-operating characteristic curve of 0.851 (95% CI 0.850-0.853). The impaired fasting glucose prediction model included six questions and achieved an area under the receiver-operating characteristic curve of 0.840 (95% CI 0.839-0.840). There were four questions that were included in both models (age, sex, waist circumference and blood sugar history), with physical activity selected only for undiagnosed Type 2 diabetes and questions on family history and hypertension drug use selected only for the impaired fasting glucose prediction model. CONCLUSIONS This study proposes two simplified models based on FINDRISC questions for screening of undiagnosed Type 2 diabetes and impaired fasting glucose in the Slovenian population. A significant improvement in performance was achieved compared with the original FINDRISC questionnaire. Both models include waist circumference instead of BMI.
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Affiliation(s)
- G Štiglic
- Faculty of Health Sciences, University of Maribor, Maribor, Slovenia
- Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
| | - P Kocbek
- Faculty of Health Sciences, University of Maribor, Maribor, Slovenia
| | - L Cilar
- Faculty of Health Sciences, University of Maribor, Maribor, Slovenia
| | - N Fijačko
- Faculty of Health Sciences, University of Maribor, Maribor, Slovenia
| | - A Stožer
- Faculty of Medicine, University of Maribor, Maribor, Slovenia
| | - J Zaletel
- Department of Endocrinology, Diabetes and Metabolic Diseases, University Medical Centre, Ljubljana, Slovenia
| | - A Sheikh
- Centre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA
| | - P Povalej Bržan
- Faculty of Health Sciences, University of Maribor, Maribor, Slovenia
- Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
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Moldobaeva MS, Vinogradova AV, Esenamanova MK. Risk of Type 2 Diabetes Mellitus Development in the Native Population of Low- and High-Altitude Regions of Kyrgyzstan: Finnish Diabetes Risc Score Questionnaire Results. High Alt Med Biol 2017; 18:428-435. [PMID: 29125907 DOI: 10.1089/ham.2017.0036] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Moldobaeva, Marina S., Anastasiya V. Vinogradova, and Marina K. Esenamanova. Risk of type 2 diabetes mellitus development in the native population of low- and high-altitude regions of Kyrgyzstan: Finnish Diabetes Risc Score questionnaire results. High Alt Med Biol. 18:428-435, 2017. OBJECTIVE The number of patients with diabetes is steadily growing, but likely only half of all cases are ever identified. The Kyrgyz, native inhabitants of Central Asia, live in the mountainous area and have a particular lifestyle and nutrition. However, the risk of type 2 diabetes mellitus (T2DM) in our population is not well defined. Therefore, we aimed at determining the risk of T2DM development in the Kyrgyz population residing in low- and high-altitude (HAlt) regions by using the Finnish Diabetes Risc Score (FINDRISC) questionnaire. METHODS We included in the study 3190 randomly selected participants, including 1780 low-altitude (LAlt) residents (Chu region, 500-1200 m) and 1410 HAlt residents (Naryn region, 2000-4500 m), among whom there were 1207 men and 1983 women. Assessment of T2DM development was conducted by using the FINDRISC questionnaire and risk stratification was performed by region of residency, gender, and age. RESULTS An irregular intake of vegetables and fruits, increased waist circumference (WC), and increased body mass index (BMI) were identified as leading risk factors of T2DM development in native residents of Chu and Naryn regions of Kyrgyzstan. The 10-year risk stratification of T2DM development revealed the absence of a very high-risk group; high-risk status was more frequently identified among residents of the LAlt Chu district (4.7% of women and 2.1% of men), as compared with the HAlt population (1.9% of women and 1% of men) (p = 0.0018 for women and p = 0.09 for men). CONCLUSIONS In the Kyrgyz population, a 10-year high risk of T2DM development is greater among residents of LAlts as compared with HAlts, irrespective of gender. No very high-risk group was detected in residents of low or HAlts. The leading composites of FINDRISC score are increased WC and BMI, possibly due to irregular intake of vegetables and fruits that are dependent on the altitude of residence and age.
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Affiliation(s)
- Marina S Moldobaeva
- 1 Department of Internal Diseases Propedeutic with Course of Endocrinology, Faculty of Medicine, Kyrgyz State Medical Academy named by I.K. Ahunbaev , Bishkek, Kyrgyzstan
| | - Anastasiya V Vinogradova
- 1 Department of Internal Diseases Propedeutic with Course of Endocrinology, Faculty of Medicine, Kyrgyz State Medical Academy named by I.K. Ahunbaev , Bishkek, Kyrgyzstan
| | - Marina K Esenamanova
- 2 Department of Hygiene Disciplines, Kyrgyz State Medical Academy named by I.K. Ahunbaev , Bishkek, Kyrgyzstan
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Fokkens BT, van Waateringe RP, Mulder DJ, Wolffenbuttel BHR, Smit AJ. Skin autofluorescence improves the Finnish Diabetes Risk Score in the detection of diabetes in a large population-based cohort: The LifeLines Cohort Study. DIABETES & METABOLISM 2017; 44:424-430. [PMID: 29097003 DOI: 10.1016/j.diabet.2017.09.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Revised: 09/17/2017] [Accepted: 09/18/2017] [Indexed: 12/15/2022]
Abstract
AIM The aim of the present study was to investigate whether skin autofluorescence would improve the Finnish Diabetes Risk Score (FINDRISC) in detecting undiagnosed diabetes in a large population-based cohort. METHODS Included were participants from the Dutch LifeLines Cohort Study. Skin autofluorescence was assessed in an unselected subset of participants using the AGE Reader. After the exclusion of participants with previously diagnosed diabetes (n=1635), pregnant women (n=58) and those using corticosteroids (n=345), 79,248 subjects were eligible for analysis. Diabetes was defined as fasting plasma glucose ≥7.0mmol/L, non-fasting plasma glucose ≥11.1mmol/L or HbA1c ≥6.5% (48mmol/mol). RESULTS Diabetes was detected in 1042 participants (aged 55±12 years; 54% male). Skin autofluorescence improved the area under the receiver operating characteristic (AUROC) curve of the FINDRISC model from 0.802 to 0.811 (P<0.001). Furthermore, the addition of skin autofluorescence to FINDRISC reclassified 8-15% of all participants into more accurate risk categories (NRI: 0.080, 95% CI: 0.052-0.110). The proportion of reclassified participants was especially high (>30%) in the intermediate (1% to <5% and 5% to<10%) risk categories. When skin autofluorescence was added to a simplified model (age+body mass index), its discriminatory performance was similar to the full model+skin autofluorescence (AUROC: 0.806, P=0.062). CONCLUSION Skin autofluorescence is a non-invasive tool that can be used to further improve the FINDRISC for diabetes detection. The new resultant model is especially useful for reclassifying people in the intermediate-risk categories, where additional blood glucose testing is needed to confirm the presence of diabetes.
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Affiliation(s)
- B T Fokkens
- Division of Vascular Medicine, Department of Internal Medicine, University of Groningen, University Medical Center Groningen (UMCG), Hanzeplein 1, 9713 GZ Groningen, Netherlands.
| | - R P van Waateringe
- Department of Endocrinology, University of Groningen, University Medical Center Groningen (UMCG), Hanzeplein 1, 9713 GZ Groningen, Netherlands
| | - D J Mulder
- Division of Vascular Medicine, Department of Internal Medicine, University of Groningen, University Medical Center Groningen (UMCG), Hanzeplein 1, 9713 GZ Groningen, Netherlands
| | - B H R Wolffenbuttel
- Department of Endocrinology, University of Groningen, University Medical Center Groningen (UMCG), Hanzeplein 1, 9713 GZ Groningen, Netherlands
| | - A J Smit
- Division of Vascular Medicine, Department of Internal Medicine, University of Groningen, University Medical Center Groningen (UMCG), Hanzeplein 1, 9713 GZ Groningen, Netherlands
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Tian X, Liu Y, Han Y, Shi J, Zhu T. Risk Score for Detecting Dysglycemia: A Cross-Sectional Study of a Working-Age Population in an Oil Field in China. Med Sci Monit 2017; 23:2833-2841. [PMID: 28601890 PMCID: PMC5475373 DOI: 10.12659/msm.904449] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Background Dysglycemia (pre-diabetes or diabetes) in young adults has increased rapidly. However, the risk scores for detecting dysglycemia in oil field staff and workers in China are limited. This study developed a risk score for the early identification of dysglycemia based on epidemiological and health examination data in an oil field working-age population with increased risk of diabetes. Material/Methods Multivariable logistic regression was used to develop the risk score model in a population-based, cross-sectional study. All subjects completed the questionnaires and underwent physical examination and oral glucose tolerance tests. The performance of the risk score models was evaluated using the area under the receiver operating characteristic curve (AUC). Results The study population consisted of 1995 participants, 20–64 years old (49.4% males), with undiagnosed diabetes or pre-diabetes who underwent periodic health examinations from March 2014 to June 2015 in Dagang oil field, Tianjin, China. Age, sex, body mass index, history of high blood glucose, smoking, triglyceride, and fasting plasma glucose (FPG) constituted the Dagang dysglycemia risk score (Dagang DRS) model. The performance of Dagang DRS was superior to m-FINDRISC (AUC: 0.791; 95% confidence interval (CI), 0.773–0.809 vs. 0.633; 95% CI, 0.611–0.654). At the cut-off value of 5.6 mmol/L, the Dagang DRS (AUC: 0.616; 95% CI, 0.592–0.641) was better than the FPG value alone (AUC: 0.571; 95% CI, 0.546–0.596) in participants with FPG <6.1 mmol/L (n=1545, P=0.028). Conclusions Dagang DRS is a valuable tool for detecting dysglycemia, especially when FPG <6.1 mmol/L, in oil field workers in China.
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Affiliation(s)
- Xiubiao Tian
- Department of Endocrinology, Tianjin Medical University General Hospital, Tianjin, China (mainland)
| | - Yan Liu
- Department of Geriatrics, Henghe Hospital, Beijing, China (mainland)
| | - Ying Han
- Department of Endocrinology, Dagang Oil Field General Hospital, Tianjin, China (mainland)
| | - Jieli Shi
- Department of Endocrinology, Dagang Oil Field General Hospital, Tianjin, China (mainland)
| | - Tiehong Zhu
- Department of Endocrinology, Tianjin Medical University General Hospital, Tianjin, China (mainland)
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Zhang L, Li R, He J, Yang Q, Wu Y, Huang J, Wu B. Co-expression analysis among microRNAs, long non-coding RNAs, and messenger RNAs to understand the pathogenesis and progression of diabetic kidney disease at the genetic level. Methods 2017; 124:46-56. [PMID: 28577935 DOI: 10.1016/j.ymeth.2017.05.023] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2017] [Revised: 05/22/2017] [Accepted: 05/28/2017] [Indexed: 01/19/2023] Open
Abstract
Diabetic kidney disease (DKD) is a serious disease that presents a major health problem worldwide. There is a desperate need to explore novel biomarkers to further facilitate the early diagnosis and effective treatment in DKD patients, thus preventing them from developing end-stage renal disease (ESRD). However, most regulation mechanisms at the genetic level in DKD still remain unclear. In this paper, we describe our innovative methodologies that integrate biological, computational, and statistical approaches to investigate important roles performed by regulations among microRNAs (miRs), long non-coding RNAs (lncRNAs), and messenger RNAs (mRNAs) in DKD. We conducted fully transparent, rigorously designed experiments. Our robust and reproducible results identified hsa-miR-223-3p as a candidate novel biomarker performing important roles in DKD disease process.
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Affiliation(s)
- Lihua Zhang
- Department of Geriatric Endocrinology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650031, China
| | - Rong Li
- Department of Nephrology, First People's Hospital of Yunnan Province, Kunming, Yunnan 650032, China
| | - Junyi He
- Department of Geriatric Endocrinology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650031, China
| | - Qiuping Yang
- Department of Geriatric Endocrinology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650031, China
| | - Yanan Wu
- Department of Geriatric Endocrinology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650031, China
| | - Jingshan Huang
- Computer Science Department, School of Computing, University of South Alabama, Mobile, AL 36688, USA
| | - Bin Wu
- Department of Endocrinology and Metabolism, First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650031, China.
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Fizelova M, Jauhiainen R, Stančáková A, Kuusisto J, Laakso M. Finnish Diabetes Risk Score Is Associated with Impaired Insulin Secretion and Insulin Sensitivity, Drug-Treated Hypertension and Cardiovascular Disease: A Follow-Up Study of the METSIM Cohort. PLoS One 2016; 11:e0166584. [PMID: 27851812 PMCID: PMC5112858 DOI: 10.1371/journal.pone.0166584] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Accepted: 10/31/2016] [Indexed: 12/25/2022] Open
Abstract
We investigated the association of the Finnish Diabetes Risk Score (FINDRISC) with insulin secretion, insulin sensitivity, and risk of type 2 diabetes, drug-treated hypertension, cardiovascular (CVD) events and total mortality in a follow-up study of the Metabolic Syndrome in Men (METSIM) cohort. The METSIM study includes 10,197 Finnish men, aged 45-73 years, and examined in 2005-2010. Of 8,749 non-diabetic participants of the METSIM study 693 developed incident type 2 diabetes, 225 started antihypertensive medication, 351 had a CVD event, and 392 died during a 8.2-year follow-up. The FINDRISC was significantly associated with decreases in insulin secretion and insulin sensitivity (P<0.0001), and with a 4.14-fold increased risk of incident type 2 diabetes, 2.43-fold increased risk of drug-treated hypertension, 1.61-fold increased risk of CVD, and 1.55-increased risk of total mortality (the FINDRISC ≥12 vs. < 12 points). In conclusion, the FINDRISC predicts impairment in insulin secretion and insulin sensitivity, the conversion to type 2 diabetes, drug-treated hypertension, CVD events and total mortality.
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Affiliation(s)
- Maria Fizelova
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Raimo Jauhiainen
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Alena Stančáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
- * E-mail:
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Salinero-Fort MA, Burgos-Lunar C, Lahoz C, Mostaza JM, Abánades-Herranz JC, Laguna-Cuesta F, Estirado-de Cabo E, García-Iglesias F, González-Alegre T, Fernández-Puntero B, Montesano-Sánchez L, Vicent-López D, Cornejo-del Río V, Fernández-García PJ, Sánchez-Arroyo V, Sabín-Rodríguez C, López-López S, Patrón-Barandio P, Gómez-Campelo P. Performance of the Finnish Diabetes Risk Score and a Simplified Finnish Diabetes Risk Score in a Community-Based, Cross-Sectional Programme for Screening of Undiagnosed Type 2 Diabetes Mellitus and Dysglycaemia in Madrid, Spain: The SPREDIA-2 Study. PLoS One 2016; 11:e0158489. [PMID: 27441722 PMCID: PMC4956208 DOI: 10.1371/journal.pone.0158489] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2016] [Accepted: 06/16/2016] [Indexed: 01/14/2023] Open
Abstract
Aim To evaluate the performance of the Finnish Diabetes Risk Score (FINDRISC) and a simplified FINDRISC score (MADRISC) in screening for undiagnosed type 2 diabetes mellitus (UT2DM) and dysglycaemia. Methods A population-based, cross-sectional, descriptive study was carried out with participants with UT2DM, ranged between 45–74 years and lived in two districts in the north of metropolitan Madrid (Spain). The FINDRISC and MADRISC scores were evaluated using the area under the receiver operating characteristic curve method (ROC-AUC). Four different gold standards were used for UT2DM and any dysglycaemia, as follows: fasting plasma glucose (FPG), oral glucose tolerance test (OGTT), HbA1c, and OGTT or HbA1c. Dysglycaemia and UT2DM were defined according to American Diabetes Association criteria. Results The study population comprised 1,426 participants (832 females and 594 males) with a mean age of 62 years (SD = 6.1). When HbA1c or OGTT criteria were used, the prevalence of UT2DM was 7.4% (10.4% in men and 5.2% in women; p<0.01) and the FINDRISC ROC-AUC for UT2DM was 0.72 (95% CI, 0.69–0.74). The optimal cut-off point was ≥13 (sensitivity = 63.8%, specificity = 65.1%). The ROC-AUC of MADRISC was 0.76 (95% CI, 0.72–0.81) with ≥13 as the optimal cut-off point (sensitivity = 84.8%, specificity = 54.6%). FINDRISC score ≥12 for detecting any dysglycaemia offered the best cut-off point when HbA1c alone or OGTT and HbA1c were the criteria used. Conclusions FINDRISC proved to be a useful instrument in screening for dysglycaemia and UT2DM. In the screening of UT2DM, the simplified MADRISC performed as well as FINDRISC.
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Affiliation(s)
- M. A. Salinero-Fort
- Subdirección General de Investigación Sanitaria, Consejería de Sanidad de Madrid, Madrid, Spain
- MADIABETES Research Group. Madrid, Spain
- Aging and Fragility in the Elderly Group- IdiPAZ, Madrid, Spain
- Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Madrid, Spain
- * E-mail:
| | - C. Burgos-Lunar
- MADIABETES Research Group. Madrid, Spain
- Aging and Fragility in the Elderly Group- IdiPAZ, Madrid, Spain
- Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Madrid, Spain
- Dirección General de Salud Pública, Subdirección de Promoción, Prevención y Educación de la Salud, Consejería de Sanidad, Madrid, Spain
| | - C. Lahoz
- Servicio de Medicina Interna, Hospital Carlos III, Madrid, Spain
| | - J. M. Mostaza
- Servicio de Medicina Interna, Hospital Carlos III, Madrid, Spain
| | - J. C. Abánades-Herranz
- MADIABETES Research Group. Madrid, Spain
- Aging and Fragility in the Elderly Group- IdiPAZ, Madrid, Spain
- Centro de Salud Monóvar, Servicio Madrileño de Salud, Madrid, Spain
| | - F. Laguna-Cuesta
- Servicio de Medicina Interna, Hospital Carlos III, Madrid, Spain
| | | | | | | | | | | | | | | | | | | | | | | | | | - P. Gómez-Campelo
- MADIABETES Research Group. Madrid, Spain
- Aging and Fragility in the Elderly Group- IdiPAZ, Madrid, Spain
- Plataforma de Apoyo al Investigador Novel (PAIN Platform), Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, Spain
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Lindström J, Uusitupa M, Tuomilehto J, Peltonen M. Following in the Footsteps of the North Karelia Project: Prevention of
Type 2 Diabetes. Glob Heart 2016; 11:223-8. [DOI: 10.1016/j.gheart.2016.04.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Accepted: 04/20/2016] [Indexed: 01/24/2023] Open
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Jølle A, Midthjell K, Holmen J, Tuomilehto J, Carlsen SM, Shaw J, Åsvold BO. Impact of sex and age on the performance of FINDRISC: the HUNT Study in Norway. BMJ Open Diabetes Res Care 2016; 4:e000217. [PMID: 27403326 PMCID: PMC4932345 DOI: 10.1136/bmjdrc-2016-000217] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2016] [Accepted: 04/14/2016] [Indexed: 01/02/2023] Open
Abstract
OBJECTIVE The Finnish Diabetes Risk Score (FINDRISC) is recommended as a screening tool for diabetes risk. However, there is a lack of well-powered studies examining the performance of FINDRISC by sex and age. We aim to estimate, by sex and age, the prevalence of elevated FINDRISC and positive predictive value (PPV) of FINDRISC for identifying impaired glucose metabolism (IGM) in a general Norwegian population. RESEARCH DESIGN AND METHODS We estimated the prevalence of elevated FINDRISC (≥15) among 47 694 adults in the third survey of the Nord-Trøndelag Health Study (HUNT3, 2006-08). Among 2559 participants who participated in oral glucose tolerance testing, we estimated the PPV of elevated FINDRISC for identifying unknown prevalent diabetes and other forms of IGM. RESULTS The prevalence of elevated FINDRISC was 12.1% in women, 9.6% in men, and increased from 1.5% at age 20-39 to 25.1% at age 70-79 years. The PPVs of elevated FINDRISC were 9.8% for diabetes, 16.9% for impaired glucose tolerance, 8.2% for impaired fasting glucose, and 34.9% for any form of IGM. The PPV for IGM was lower in women (31.2%) than in men (40.4%), and increased from 19.1% at age 20-39 to 55.5% at age ≥80 years. CONCLUSIONS FINDRISC identified more women than men as high-risk individuals for diabetes. FINDRISC had a high PPV for detecting prevalent IGM, and the PPV was higher in men than in women and in the older individuals. Our data indicate that the impact of sex and age on diabetes risk is not fully captured by FINDRISC, and that refinements to it might improve diabetes prediction.
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Affiliation(s)
- Anne Jølle
- Faculty of Medicine, Department of Public Health and General Practice , HUNT Research Centre, NTNU, Norwegian University of Science and Technology , Levanger , Norway
| | - Kristian Midthjell
- Faculty of Medicine, Department of Public Health and General Practice , HUNT Research Centre, NTNU, Norwegian University of Science and Technology , Levanger , Norway
| | - Jostein Holmen
- Faculty of Medicine, Department of Public Health and General Practice , HUNT Research Centre, NTNU, Norwegian University of Science and Technology , Levanger , Norway
| | - Jaakko Tuomilehto
- Dasman Diabetes Insitute, Dasman, Kuwait; Department for Clinical Neurosciences and Preventive Medicine, Danube University Krems, Krems an der Donau, Austria; Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland; Department of Public Health, University of Helsinki, Helsinki, Finland; Saudi Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Sven M Carlsen
- Department of Endocrinology, St Olavs Hospital, Trondheim University Hospital, Trondheim, Norway; Unit for Applied Clinical Research, Institute for Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jonathan Shaw
- Baker IDI, Heart and Diabetes Institute , Melbourne , Australia
| | - Bjørn O Åsvold
- Faculty of Medicine, Department of Public Health and General Practice, HUNT Research Centre, NTNU, Norwegian University of Science and Technology, Levanger, Norway; Department of Endocrinology, St Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
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Fijacko N, Brzan PP, Stiglic G. Mobile Applications for Type 2 Diabetes Risk Estimation: a Systematic Review. J Med Syst 2015; 39:124. [PMID: 26303152 DOI: 10.1007/s10916-015-0319-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2015] [Accepted: 08/12/2015] [Indexed: 10/23/2022]
Abstract
Screening for chronical diseases like type 2 diabetes can be done using different methods and various risk tests. This study present a review of type 2 diabetes risk estimation mobile applications focusing on their functionality and availability of information on the underlying risk calculators. Only 9 out of 31 reviewed mobile applications, featured in three major mobile application stores, disclosed the name of risk calculator used for assessing the risk of type 2 diabetes. Even more concerning, none of the reviewed applications mentioned that they are collecting the data from users to improve the performance of their risk estimation calculators or offer users the descriptive statistics of the results from users that already used the application. For that purpose the questionnaires used for calculation of risk should be upgraded by including the information on the most recent blood sugar level measurements from users. Although mobile applications represent a great future potential for health applications, developers still do not put enough emphasis on informing the user of the underlying methods used to estimate the risk for a specific clinical condition.
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Affiliation(s)
- Nino Fijacko
- Faculty of Health Sciences, University of Maribor, Zitna ulica 15, 2000, Maribor, Slovenia,
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Salinero-Fort MÁ, de Burgos-Lunar C, Mostaza Prieto J, Lahoz Rallo C, Abánades-Herranz JC, Gómez-Campelo P, Laguna Cuesta F, Estirado De Cabo E, García Iglesias F, González Alegre T, Fernández Puntero B, Montesano Sánchez L, Vicent López D, Cornejo Del Río V, Fernández García PJ, Sabín Rodríguez C, López López S, Patrón Barandío P. Validating prediction scales of type 2 diabetes mellitus in Spain: the SPREDIA-2 population-based prospective cohort study protocol. BMJ Open 2015; 5:e007195. [PMID: 26220868 PMCID: PMC4521512 DOI: 10.1136/bmjopen-2014-007195] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
INTRODUCTION The incidence of type 2 diabetes mellitus (T2DM) is increasing worldwide. When diagnosed, many patients already have organ damage or advance subclinical atherosclerosis. An early diagnosis could allow the implementation of lifestyle changes and treatment options aimed at delaying the progression of the disease and to avoid cardiovascular complications. Different scores for identifying undiagnosed diabetes have been reported, however, their performance in populations of southern Europe has not been sufficiently evaluated. The main objectives of our study are: to evaluate the screening performance and cut-off points of the main scores that identify the risk of undiagnosed T2DM and prediabetes in a Spanish population, and to develop and validate our own predictive models of undiagnosed T2DM (screening model), and future T2DM (prediction risk model) after 5-year follow-up. As a secondary objective, we will evaluate the atherosclerotic burden of the population with undiagnosed T2DM. METHODS AND ANALYSIS Population-based prospective cohort study with baseline screening, to evaluate the performance of the FINDRISC, DANISH, DESIR, ARIC and QDScore, against the gold standard tests: Fasting plasma glucose, oral glucose tolerance and/or HbA1c. The sample size will include 1352 participants between the ages of 45 and 74 years. ANALYSIS sensitivity, specificity, positive predictive value, negative predictive value, likelihood ratio positive, likelihood ratio negative and receiver operating characteristic curves and area under curve. Binary logistic regression for the first 700 individuals (derivation) and last 652 (validation) will be performed. All analyses will be calculated with their 95% CI; statistical significance will be p<0.05. ETHICS AND DISSEMINATION The study protocol has been approved by the Research Ethics Committee of the Carlos III Hospital (Madrid). The score performance and predictive model will be presented in medical conferences, workshops, seminars and round table discussions. Furthermore, the predictive model will be published in a peer-reviewed medical journal to further increase the exposure of the scores.
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Affiliation(s)
- Miguel Ángel Salinero-Fort
- Gerencia Adjunta de Planificación y Calidad, Atención Primaria. Servicio Madrileño de Salud, Instituto de Investigación Sanitaria del Hospital Universitario La Paz-IdiPAZ. Red de Investigación en servicios de salud en enfermedades crónicas (REDISSEC), Madrid, Spain
| | - Carmen de Burgos-Lunar
- Servicio de Medicina Preventiva, Hospital Universitario La Paz, Instituto de Investigación Sanitaria del Hospital Universitario La Paz-IdiPAZ. Red de Investigación en servicios de salud en enfermedades crónicas (REDISSEC), Madrid, Spain
| | | | | | - Juan Carlos Abánades-Herranz
- Dirección Técnica de Docencia e Investigación. Gerencia Adjunta de Planificación y Calidad. Atención Primaria, Servicio Madrileño de Salud. Instituto de Investigación Sanitaria del Hospital Universitario La Paz-IdiPaz, Madrid, Spain
| | - Paloma Gómez-Campelo
- Plataforma de apoyo al Investigador Novel. Instituto de Investigación Sanitaria del Hospital Universitario La Paz-IdiPAZ, Madrid, Spain
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Van Olmen J, Marie KG, Christian D, Clovis KJ, Emery B, Maurits VP, Heang H, Kristien VA, Natalie E, François S, Guy K. Content, participants and outcomes of three diabetes care programmes in three low and middle income countries. Prim Care Diabetes 2015; 9:196-202. [PMID: 25281167 DOI: 10.1016/j.pcd.2014.09.001] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2014] [Revised: 08/13/2014] [Accepted: 09/08/2014] [Indexed: 01/02/2023]
Abstract
AIMS To improve access and quality of diabetes care for people in low-income countries, it is important to understand which elements of diabetes care are effective. This paper analyses three diabetes care programmes in the DR Congo, Cambodia and the Philippines. METHODS Three programmes offering diabetes care and self-management were selected. Programme information was collected through document review and interviews. Data about participants' characteristics, health outcomes, care utilisation, expenditures, care perception and self-management were extracted from a study database. Comparative univariate analyses were performed. RESULTS Kin-réseau (DR Congo) is an urban primary care network with 8000 patients. MoPoTsyo (Cambodia) is a community-based peer educator network, covering 7000 patients. FiLDCare (Philippines) is a programme in which 1000 patients receive care in a health facility and self-management support from a community health worker. Content of care of the programmes is comparable, the focus on self-management largest in MoPoTsyo. On average, Kin-réseau patients have a higher age, longer diabetes history and more overweight. MoPoTsyo includes most female, most illiterate and most lean patients. Health outcomes (HbA1C level, systolic blood pressure, diabetes foot lesions) were most favourable for MoPoTsyo patients. Diabetes-related health care expenditure was highest for FiLDCare patients. CONCLUSIONS This study shows it possible to maintain a diabetes programme with minimal external resources, offering care and self-management support. It also illustrates that health outcomes of persons with diabetes are determined by their bio-psycho-social characteristics and behaviour, which are each subject to the content of care and the approach to chronic illness and self-management of the programme, in turn influenced by the larger context.
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Affiliation(s)
- Josefien Van Olmen
- Institute of Tropical Medicine, Department of Public Health Antwerp, Belgium; Department of General Practice & Elderly Medicine, EMGO, Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands.
| | - Ku Grace Marie
- Institute of Tropical Medicine, Department of Public Health Antwerp, Belgium
| | | | | | - Bewa Emery
- Memisa, Kinshasa, People's Republic of Congo
| | | | | | - Van Acker Kristien
- Algemeen Ziekenhuis Heilige Familie, Reet & Centre de Santé des Fagnes, Chimay, Belgium
| | | | - Schellevis François
- Department of General Practice & Elderly Medicine, EMGO, Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands; NIVEL (Netherlands Institute for Health Services Research), The Netherlands
| | - Kegels Guy
- Institute of Tropical Medicine, Department of Public Health Antwerp, Belgium
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Masconi KL, Matsha TE, Echouffo-Tcheugui JB, Erasmus RT, Kengne AP. Reporting and handling of missing data in predictive research for prevalent undiagnosed type 2 diabetes mellitus: a systematic review. EPMA J 2015; 6:7. [PMID: 25829972 PMCID: PMC4380106 DOI: 10.1186/s13167-015-0028-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2014] [Accepted: 02/07/2015] [Indexed: 01/10/2023]
Abstract
Missing values are common in health research and omitting participants with missing data often leads to loss of statistical power, biased estimates and, consequently, inaccurate inferences. We critically reviewed the challenges posed by missing data in medical research and approaches to address them. To achieve this more efficiently, these issues were analyzed and illustrated through a systematic review on the reporting of missing data and imputation methods (prediction of missing values through relationships within and between variables) undertaken in risk prediction studies of undiagnosed diabetes. Prevalent diabetes risk models were selected based on a recent comprehensive systematic review, supplemented by an updated search of English-language studies published between 1997 and 2014. Reporting of missing data has been limited in studies of prevalent diabetes prediction. Of the 48 articles identified, 62.5% (n = 30) did not report any information on missing data or handling techniques. In 21 (43.8%) studies, researchers opted out of imputation, completing case-wise deletion of participants missing any predictor values. Although imputation methods are encouraged to handle missing data and ensure the accuracy of inferences, this has seldom been the case in studies of diabetes risk prediction. Hence, we elaborated on the various types and patterns of missing data, the limitations of case-wise deletion and state-of the-art methods of imputations and their challenges. This review highlights the inexperience or disregard of investigators of the effect of missing data in risk prediction research. Formal guidelines may enhance the reporting and appropriate handling of missing data in scientific journals.
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Affiliation(s)
- Katya L Masconi
- Division of Chemical Pathology, Faculty of Health Sciences, National Health Laboratory Service (NHLS) and University of Stellenbosch, Cape Town, South Africa ; Non-Communicable Diseases Research Unit, South African Medical Research Council, PO Box 19070, , Tygerberg, 7505 Cape Town, South Africa
| | - Tandi E Matsha
- Department of Biomedical Technology, Faculty of Health and Wellness Sciences, Cape Peninsula University of Technology, Cape Town, South Africa
| | - Justin B Echouffo-Tcheugui
- Hubert Department of Public Health, Rollins School of Public Health, Emory University, Atlanta, GA USA ; Department of Medicine, MedStar Health System, Baltimore, MD USA
| | - Rajiv T Erasmus
- Division of Chemical Pathology, Faculty of Health Sciences, National Health Laboratory Service (NHLS) and University of Stellenbosch, Cape Town, South Africa
| | - Andre P Kengne
- Non-Communicable Diseases Research Unit, South African Medical Research Council, PO Box 19070, , Tygerberg, 7505 Cape Town, South Africa ; Department of Medicine, University of Cape Town, Cape Town, South Africa
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Implementing elements of a context-adapted chronic care model to improve first-line diabetes care: effects on assessment of chronic illness care and glycaemic control among people with diabetes enrolled to the First-Line Diabetes Care (FiLDCare) Project in the Northern Philippines. Prim Health Care Res Dev 2015; 16:481-91. [DOI: 10.1017/s1463423614000553] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
AimThe purpose of this study was to investigate the effects of implementing elements of a context-adapted chronic disease-care model (CACCM) in two local government primary healthcare units of a non-highly urbanized city and a rural municipality in the Philippines on Patients’ Assessment of Chronic Illness Care (PACIC) and glycaemic control (HbA1c) of people with diabetes.BackgroundLow-to-middle income countries like the Philippines are beset with rising prevalence of chronic conditions but their healthcare systems are still acute disease oriented. Attention towards improving care for chronic conditions particularly in primary healthcare is imperative and ways by which this can be done amidst resource constraints need to be explored.MethodsA chronic care model was adapted based on the context of the Philippines. Selected elements (community sensitization, decision support, minor re-organization of health services, health service delivery-system re-design, and self-management education and support) were implemented. PACIC and HbA1c were measured before and one year after the start of implementation.FindingsThe improvements in the PACIC (median, from 3.2 to 3.5) as well as in four of the five subsets of the PACIC were statistically significant (P-values: PACIC=0.009; ‘patient activation’=0.026; ‘goal setting’=0.017; ‘problem solving’<0.001; ‘follow-up’<0.001). The decrease in HbA1c (median, from 7.7% to 6.9%) and the level of diabetes control of the project participants (increase of optimally controlled diabetes from 37.2% to 50.6%) were likewise significant (P<0.000 andP=0.014). A significantly higher rating of the post-implementation PACIC subsets ‘problem solving’ (P=0.027) and ‘follow-up’ (P=0.025) was noted among those participants whose HbA1c improved. The quality of chronic care in general and primary diabetes care in particular may be improved, as measured through the PACIC and glycaemic control, in resource-constrained settings applying selected elements of a CACCM and without causing much strain on an already-burdened healthcare system.
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Maskarinec G, Jacobs S, Morimoto Y, Chock M, Grandinetti A, Kolonel LN. Disparity in diabetes risk across Native Hawaiians and different Asian groups: the multiethnic cohort. Asia Pac J Public Health 2014; 27:375-84. [PMID: 25164594 DOI: 10.1177/1010539514548757] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
We evaluated the impact of body mass index (BMI) and lifestyle risk factors on ethnic disparity in diabetes incidence among 89 198 Asian, Native Hawaiian, and white participants of the Multiethnic Cohort who completed multiple questionnaires. After 12 years of follow-up, 11 218 new cases were identified through self-report and health plan linkages. BMI was lowest in Chinese/Koreans, Japanese, and Filipinos (22.4, 23.5, and 23.9 kg/m(2)). Using Cox regression, the unadjusted hazard ratios were 1.9 (Chinese/Korean), 2.1 (Japanese, Mixed-Asian), 2.2 (Filipino), 2.5 (Native Hawaiian), and 2.6 (part-Asian) as compared with whites. With BMI added, the risk for Japanese, Filipinos, Chinese/Koreans, and mixed-Asians increased (8%-42%) but declined in part-Asians and Native Hawaiians (17%-31%). When lifestyle and dietary factors were also included, the risk was attenuated in all groups (6%-14%). Despite their lower BMI, Asian Americans have a higher diabetes risk than whites, but dietary and lifestyle factors do not account for the excess risk.
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Affiliation(s)
| | - Simone Jacobs
- German Institute of Human Nutrition, Potsdam-Rehbrücke, Germany
| | | | - Marci Chock
- University of Hawaii Cancer Center, Honolulu, HI, USA
| | | | - Laurence N Kolonel
- Office of Public Health Studies, University of Hawaii, Honolulu, HI, USA
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Zhang L, Zhang Z, Zhang Y, Hu G, Chen L. Evaluation of Finnish Diabetes Risk Score in screening undiagnosed diabetes and prediabetes among U.S. adults by gender and race: NHANES 1999-2010. PLoS One 2014; 9:e97865. [PMID: 24852786 PMCID: PMC4031122 DOI: 10.1371/journal.pone.0097865] [Citation(s) in RCA: 83] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2014] [Accepted: 04/25/2014] [Indexed: 12/25/2022] Open
Abstract
Objective To evaluate the performance of Finnish Diabetes Risk Score (FINDRISC) in detecting undiagnosed diabetes and prediabetes among U.S. adults by gender and race. Methods This cross-sectional analysis included participants (aged ≥20 years) from the National Health and Nutrition Examination Survey (NHANES) 1999–2010. Sensitivity, specificity, area under the receiver operating characteristic (ROC) curve and the optimal cutoff points for identifying undiagnosed diabetes and prediabetes were calculated for FINDRISC by gender and race/ethnicity. Results Among the 20,633 adults (≥20 years), 49.8% were women and 53.0% were non-Hispanic White. The prevalence of undiagnosed diabetes and prediabetes was 4.1% and 35.6%, respectively. FINDRISC was positively associated with the prevalence of diabetes (OR = 1.48 for 1 unit increase, p<0.001) and prediabetes (OR = 1.15 for 1 unit increase, p<0.001). The area under ROC for detecting undiagnosed diabetes was 0.75 for total population, 0.74 for men and 0.78 for women (p = 0.04); 0.76 for White, 0.76 for Black and 0.72 for Hispanics (p = 0.03 for White vs. Hispanics). The area under ROC for detecting prediabetes was 0.67 for total population, 0.66 for men and 0.70 for women (p<0.001); 0.68 for White, 0.67 for Black and 0.65 for Hispanics (p<0.001 for White vs. Hispanics). The optimal cutoff point was 10 (sensitivity = 0.75) for men and 12 (sensitivity = 0.72) for women for detecting undiagnosed diabetes; 9 (sensitivity = 0.61) for men and 10 (sensitivity = 0.69) for women for detecting prediabetes. Conclusions FINDRISC is a simple and non-invasive screening tool to identify individuals at high risk for diabetes in the U.S. adults.
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Affiliation(s)
- Lu Zhang
- Epidemiology Program, School of Public Health, Louisiana State University Health Sciences Center, New Orleans, Louisiana, United States of America
| | - Zhenzhen Zhang
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan, United States of America
| | - Yurong Zhang
- The First Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, Shanxi, China
| | - Gang Hu
- Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Liwei Chen
- Department of Public Health Sciences, Clemson University, Clemson, South Carolina, United States of America
- * E-mail:
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