Identifying Heterogeneity of Diabetics Mellitus Based on the Demographical and Clinical Characteristics

Abstract Background: Diabetes is a long-term disease, which is characterised by high blood sugar and has risen as a public health problem worldwide. It may prompt a variety of serious illnesses, including stroke, kidney failure, and heart attacks. In 2014, diabetes affected approximately 422 million...

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Main Authors: Linta Islam, Md Rafiqul Islam, Shanjita Akter, Md Zobaer Hasan, Mohammad Ali Moni, Mohammed Nasir Uddin
Format: Article
Language:English
Published: Springer Nature 2022-05-01
Series:Human-Centric Intelligent Systems
Subjects:
Online Access:https://doi.org/10.1007/s44230-022-00003-1
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author Linta Islam
Md Rafiqul Islam
Shanjita Akter
Md Zobaer Hasan
Mohammad Ali Moni
Mohammed Nasir Uddin
author_facet Linta Islam
Md Rafiqul Islam
Shanjita Akter
Md Zobaer Hasan
Mohammad Ali Moni
Mohammed Nasir Uddin
author_sort Linta Islam
collection DOAJ
description Abstract Background: Diabetes is a long-term disease, which is characterised by high blood sugar and has risen as a public health problem worldwide. It may prompt a variety of serious illnesses, including stroke, kidney failure, and heart attacks. In 2014, diabetes affected approximately 422 million people worldwide and it is expected to hit 642 million people in 2040. The aim of this study is to analyse the effect of demographical and clinical characteristics for diabetics disease in Bangladesh. Methods: This study employs the quantitative approach for data analysis. First, we analyse differences in variables between diabetic patients and controls by independent two-sample t-test for continuous variables and Pearson Chi-square test for categorical variables. Then, logistic regression (LR) identifies the risk factors for diabetes disease based on the odds ratio (OR) and the adjusted odds ratio (AOR). Results: The results of the t-test and Chi square test identify that the factors: residence, wealth index, education, working status, smoking status, arm circumference, weight and BMI group show statistically (p < 0.05) significant differences between the diabetic group and the control group. And, LR model demonstrates that 2 factors (“working status” and “smoking status”) out of 13 are the significant risk factors for diabetes disease in Bangladesh. Conclusions: We believe that our analysis can help the government to take proper preparation to tackle the potentially unprecedented situations in Bangladesh.
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spelling doaj.art-c7ac31035c1b47f9923318790fed38da2023-11-05T12:20:31ZengSpringer NatureHuman-Centric Intelligent Systems2667-13362022-05-0121-2445410.1007/s44230-022-00003-1Identifying Heterogeneity of Diabetics Mellitus Based on the Demographical and Clinical CharacteristicsLinta Islam0Md Rafiqul Islam1Shanjita Akter2Md Zobaer Hasan3Mohammad Ali Moni4Mohammed Nasir Uddin5Department of CSE, Jagannath UniversityAdvanced Analytics Institute (AAi), University of Technology Sydney (UTS)Department of CSE, Islamic University of Technology (IUT)School of Science, Monash University MalaysiaSchool of Health and Rehabilitation Sciences, The University of QueenslandDepartment of CSE, Jagannath UniversityAbstract Background: Diabetes is a long-term disease, which is characterised by high blood sugar and has risen as a public health problem worldwide. It may prompt a variety of serious illnesses, including stroke, kidney failure, and heart attacks. In 2014, diabetes affected approximately 422 million people worldwide and it is expected to hit 642 million people in 2040. The aim of this study is to analyse the effect of demographical and clinical characteristics for diabetics disease in Bangladesh. Methods: This study employs the quantitative approach for data analysis. First, we analyse differences in variables between diabetic patients and controls by independent two-sample t-test for continuous variables and Pearson Chi-square test for categorical variables. Then, logistic regression (LR) identifies the risk factors for diabetes disease based on the odds ratio (OR) and the adjusted odds ratio (AOR). Results: The results of the t-test and Chi square test identify that the factors: residence, wealth index, education, working status, smoking status, arm circumference, weight and BMI group show statistically (p < 0.05) significant differences between the diabetic group and the control group. And, LR model demonstrates that 2 factors (“working status” and “smoking status”) out of 13 are the significant risk factors for diabetes disease in Bangladesh. Conclusions: We believe that our analysis can help the government to take proper preparation to tackle the potentially unprecedented situations in Bangladesh.https://doi.org/10.1007/s44230-022-00003-1Diabetes detectionQuantitative analysisLogistic regressionSignificance p-valueOdds ratioAdjusted odds ratio
spellingShingle Linta Islam
Md Rafiqul Islam
Shanjita Akter
Md Zobaer Hasan
Mohammad Ali Moni
Mohammed Nasir Uddin
Identifying Heterogeneity of Diabetics Mellitus Based on the Demographical and Clinical Characteristics
Human-Centric Intelligent Systems
Diabetes detection
Quantitative analysis
Logistic regression
Significance p-value
Odds ratio
Adjusted odds ratio
title Identifying Heterogeneity of Diabetics Mellitus Based on the Demographical and Clinical Characteristics
title_full Identifying Heterogeneity of Diabetics Mellitus Based on the Demographical and Clinical Characteristics
title_fullStr Identifying Heterogeneity of Diabetics Mellitus Based on the Demographical and Clinical Characteristics
title_full_unstemmed Identifying Heterogeneity of Diabetics Mellitus Based on the Demographical and Clinical Characteristics
title_short Identifying Heterogeneity of Diabetics Mellitus Based on the Demographical and Clinical Characteristics
title_sort identifying heterogeneity of diabetics mellitus based on the demographical and clinical characteristics
topic Diabetes detection
Quantitative analysis
Logistic regression
Significance p-value
Odds ratio
Adjusted odds ratio
url https://doi.org/10.1007/s44230-022-00003-1
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