Path Modelling of Antecedent of Diabetes Mellitus on Blood Glucose Measurements

Diabetes Mellitus (DM) is one of the non-communicable diseases and public health problems facing the worldwide population that includes Malaysia. Hitherto, the prevalence of DM becomes worsening with an estimated of 3.4 million Malaysians are diabetes sufferers and expectedly increasing year by year...

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Main Authors:	Humaira, Abdul Latif, Mohd Rashid, Ab Hamid, Noor Azlinna, Azizan, Abdul Aziz, Jemain
Format:	Conference or Workshop Item
Language:	English
Published:	AIP Publishing 2017
Subjects:	Q Science (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/23784/ http://umpir.ump.edu.my/id/eprint/23784/ http://umpir.ump.edu.my/id/eprint/23784/1/Path%20modelling%20of%20antecedent%20of%20diabetes%20mellitus%20on%20blood%20glucose%20measurements1.pdf

id	ump-23784
recordtype	eprints
spelling	ump-237842019-01-15T01:51:25Z http://umpir.ump.edu.my/id/eprint/23784/ Path Modelling of Antecedent of Diabetes Mellitus on Blood Glucose Measurements Humaira, Abdul Latif Mohd Rashid, Ab Hamid Noor Azlinna, Azizan Abdul Aziz, Jemain Q Science (General) Diabetes Mellitus (DM) is one of the non-communicable diseases and public health problems facing the worldwide population that includes Malaysia. Hitherto, the prevalence of DM becomes worsening with an estimated of 3.4 million Malaysians are diabetes sufferers and expectedly increasing year by year. Thus, this study is of great importance by regressing the medical factors that affect the blood glucose level using structural equation modelling (SEM). The SEM with partial least squares (PLS) estimation was applied to a secondary data of 644 respondents, aged ≥ 18 years in Malaysia. The data were collected in 2011 by Ministry of Health Malaysia (MOH). The variables under study are blood glucose level, cholesterol level (CL), systolic blood pressure (SBP), diastolic blood pressure (DBP), waist circumference (WC) and body mass index (BMI). From the modelling analysis, it showed that the cholesterol level (CL), systolic blood pressure (SBP) and waist circumference (WC) showed a positive significant relationship p < 0.01 (one-tailed) in influencing the blood sugar level. Whereas, diastolic blood pressure (DBP) is positively significant at p < 0.05 (one-tailed) and body mass index (BMI) is significant at p < 0.10 (one-tailed) towards blood glucose level. In conclusions, the findings from this study revealed the most salient predictors for blood glucose level which are CL, SBP and WC for diabetes mellitus among adults. AIP Publishing 2017 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/23784/1/Path%20modelling%20of%20antecedent%20of%20diabetes%20mellitus%20on%20blood%20glucose%20measurements1.pdf Humaira, Abdul Latif and Mohd Rashid, Ab Hamid and Noor Azlinna, Azizan and Abdul Aziz, Jemain (2017) Path Modelling of Antecedent of Diabetes Mellitus on Blood Glucose Measurements. In: AIP Conference Proceedings: The 3rd ISM International Statistical Conference 2016 (ISM-III), 9-11 August 2016 , Kuala Lumpur, Malaysia. pp. 1-10., 1842 (020008). ISBN 978-0-7354-1512-6 https://doi.org/10.1063/1.4982838
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	Q Science (General)
spellingShingle	Q Science (General) Humaira, Abdul Latif Mohd Rashid, Ab Hamid Noor Azlinna, Azizan Abdul Aziz, Jemain Path Modelling of Antecedent of Diabetes Mellitus on Blood Glucose Measurements
description	Diabetes Mellitus (DM) is one of the non-communicable diseases and public health problems facing the worldwide population that includes Malaysia. Hitherto, the prevalence of DM becomes worsening with an estimated of 3.4 million Malaysians are diabetes sufferers and expectedly increasing year by year. Thus, this study is of great importance by regressing the medical factors that affect the blood glucose level using structural equation modelling (SEM). The SEM with partial least squares (PLS) estimation was applied to a secondary data of 644 respondents, aged ≥ 18 years in Malaysia. The data were collected in 2011 by Ministry of Health Malaysia (MOH). The variables under study are blood glucose level, cholesterol level (CL), systolic blood pressure (SBP), diastolic blood pressure (DBP), waist circumference (WC) and body mass index (BMI). From the modelling analysis, it showed that the cholesterol level (CL), systolic blood pressure (SBP) and waist circumference (WC) showed a positive significant relationship p < 0.01 (one-tailed) in influencing the blood sugar level. Whereas, diastolic blood pressure (DBP) is positively significant at p < 0.05 (one-tailed) and body mass index (BMI) is significant at p < 0.10 (one-tailed) towards blood glucose level. In conclusions, the findings from this study revealed the most salient predictors for blood glucose level which are CL, SBP and WC for diabetes mellitus among adults.
format	Conference or Workshop Item
author	Humaira, Abdul Latif Mohd Rashid, Ab Hamid Noor Azlinna, Azizan Abdul Aziz, Jemain
author_facet	Humaira, Abdul Latif Mohd Rashid, Ab Hamid Noor Azlinna, Azizan Abdul Aziz, Jemain
author_sort	Humaira, Abdul Latif
title	Path Modelling of Antecedent of Diabetes Mellitus on Blood Glucose Measurements
title_short	Path Modelling of Antecedent of Diabetes Mellitus on Blood Glucose Measurements
title_full	Path Modelling of Antecedent of Diabetes Mellitus on Blood Glucose Measurements
title_fullStr	Path Modelling of Antecedent of Diabetes Mellitus on Blood Glucose Measurements
title_full_unstemmed	Path Modelling of Antecedent of Diabetes Mellitus on Blood Glucose Measurements
title_sort	path modelling of antecedent of diabetes mellitus on blood glucose measurements
publisher	AIP Publishing
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/23784/ http://umpir.ump.edu.my/id/eprint/23784/ http://umpir.ump.edu.my/id/eprint/23784/1/Path%20modelling%20of%20antecedent%20of%20diabetes%20mellitus%20on%20blood%20glucose%20measurements1.pdf
first_indexed	2023-09-18T22:35:47Z
last_indexed	2023-09-18T22:35:47Z
_version_	1777416585547350016

Path Modelling of Antecedent of Diabetes Mellitus on Blood Glucose Measurements

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