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

Islam, L; Islam, MR; Akter, S; Hasan, MZ; Moni, MA; Uddin, MN

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

Islam, L Islam, MR Akter, S Hasan, MZ Moni, MA Uddin, MN

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Publisher:: Springer Nature
Publication Type:: Journal Article
Citation:: Human-Centric Intelligent Systems, 2022, 2, (1-2), pp. 44-54
Issue Date:: 2022-05-12

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Field	Value	Language
dc.contributor.author	Islam, L
dc.contributor.author	Islam, MR
dc.contributor.author	Akter, S
dc.contributor.author	Hasan, MZ
dc.contributor.author	Moni, MA
dc.contributor.author	Uddin, MN
dc.date.accessioned	2023-07-05T01:00:00Z
dc.date.available	2023-07-05T01:00:00Z
dc.date.issued	2022-05-12
dc.identifier.citation	Human-Centric Intelligent Systems, 2022, 2, (1-2), pp. 44-54
dc.identifier.issn	2667-1336
dc.identifier.issn	2667-1336
dc.identifier.uri	http://hdl.handle.net/10453/171187
dc.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.
dc.language	en
dc.publisher	Springer Nature
dc.relation.ispartof	Human-Centric Intelligent Systems
dc.relation.isbasedon	10.1007/s44230-022-00003-1
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Identifying Heterogeneity of Diabetics Mellitus Based on the Demographical and Clinical Characteristics
dc.type	Journal Article
utslib.citation.volume	2
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2023-07-05T00:59:59Z
pubs.issue	1-2
pubs.publication-status	Published
pubs.volume	2
utslib.citation.issue	1-2

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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http://hdl.handle.net/10453/171187