Evidence map›Paper›PMID 26543541›Full record

ArticleJournal of diabetes investigation2015

Simple risk score to detect rural Asian Indian (Bangladeshi) adults at high risk for type 2 diabetes.

Bishwajit Bhowmik, Afroza Akhter, Liaquat Ali, Tofail Ahmed, Faruque Pathan, Hajera Mahtab, Abul Kalam Azad Khan, Akhtar Hussain

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Article in Journal of diabetes investigation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Bishwajit BhowmikDepartment of International Health, University of Oslo Oslo, Norway.
Afroza AkhterDepartment of Epidemiology & Biostatistics, Bangladesh Institute of Health Sciences (BIHS) Mirpur, Bangladesh.
Liaquat AliDepartment of Biochemistry & Cell Biology, BUHS Mirpur, Bangladesh.
Tofail AhmedDepartment of Endocrinology, Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM) Dhaka, Bangladesh.
Faruque PathanDepartment of Endocrinology, Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM) Dhaka, Bangladesh.
Hajera MahtabDepartment of Endocrinology, Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM) Dhaka, Bangladesh.
Abul Kalam Azad KhanDepartment of Endocrinology, Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM) Dhaka, Bangladesh.
Akhtar HussainDepartment of International Health, University of Oslo Oslo, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AIMS/

introductionTo develop and evaluate a simple, non-invasive, diabetes risk score for detecting individuals at high risk for type 2 diabetes in rural Bangladesh. MATERIALS AND

methodsData from 2,293 randomly selected individuals aged ≥20 years from a cross-sectional study in a rural community of Bangladesh (2009 Chandra Rural Study) was used for model development. The validity of the model was assessed in another rural cross-sectional study (2009 Thakurgaon Rural Study). The logistic regression model used included age, sex, body mass index, waist-to-hip ratio and hypertension status to predict individuals who were at high risk for type 2 diabetes.

resultsOn applying the developed model to both cohorts, the area under the receiver operating characteristic curve was 0.70 (95% confidence interval 0.68-0.72) for the Chandra cohort and 0.71 (95% confidence interval 0.68-0.74) for the Thakurgaon cohort. The risk score of >9 was shown to have the optimal cut-point to detect diabetes. This score had a sensitivity of 62.4 and 75.7%, and specificity of 67.4 and 61.6% in the two cohorts, respectively. This risk score was shown to have improved sensitivity and specificity to detect type 2 diabetes cases compared with the Thai, Indian, Omani, UK, Dutch, Portuguese and Pakistani diabetes risk scores.

conclusionsThis simple, non-invasive risk score can be used to detect individuals at high risk for type 2 diabetes in rural Bangladesh. Subjects with a score of 9 or above (out of 15) should undergo an oral glucose tolerance test for definitive diagnosis of diabetes.

Indexed as

Risk scoreRural Asian IndianType 2 diabetes

Identifiers

PMID26543541
PMCPMC4627544

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.