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Analisis Meta Hubungan antara Obesitas dan Risiko Diabetes Mellitus dengan Data Binary dan Odd Ratio menggunakan Model Random Effect

Mathematical Sciences and Applications Journal · Vol. 4 No. 2 (2024) · hlm. 83–91

DOI
10.22437/msa.v4i2.28287
ISSN
2988-6481
Terbit
2024-04-30
Penerbit
Department of Mathematics, Faculty of Science and Technology Universitas Jambi
Bahasa
en

Abstrak

Meta-analysis is a statistical technique used to combine the results of several primary studies that have been conducted previously, with the aim of obtaining stronger and more accurate conclusions than can be obtained from each primary study individually. In this case, meta-analysis is performed to evaluate the relationship between obesity and the risk of diabetes mellitus. The data used in this meta-analysis is binary data, which contains information about the presence or absence of diabetes mellitus in individuals who are obese. The odds ratio is used as a measure of effect, which is the ratio between the likelihood of diabetes mellitus in individuals who are obese compared to individuals who are not obese. The results of the meta-analysis show heterogeneity between the primary studies conducted. Therefore, random effects are used in the meta-analysis model. The results of the analysis show that there is a significant relationship between obesity and the risk of diabetes mellitus, with a high odds ratio value. The conclusion from this meta-analysis is that obesity significantly increases the risk of diabetes mellitus. This finding has important implications in efforts to prevent and treat diabetes mellitus, especially in individuals at high risk for obesity.

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  • Institut Teknologi Sepuluh Nopember
  • Bandung Institute of Technology
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Sumber metadata: OAI-PMH (metadata jurnal) https://online-journal.unja.ac.id/index.php/msa/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">Analisis Meta Hubungan antara Obesitas dan Risiko Diabetes Mellitus dengan Data Binary dan Odd Ratio menggunakan Model Random Effect</dc:title>
	<dc:creator xml:lang="en">Jiblathar, Panji</dc:creator>
	<dc:creator xml:lang="en">Agustina, Ellys</dc:creator>
	<dc:subject xml:lang="en">Effect size</dc:subject>
	<dc:subject xml:lang="en">Random effect</dc:subject>
	<dc:subject xml:lang="en">Obesity</dc:subject>
	<dc:subject xml:lang="en">Diabetes mellitus</dc:subject>
	<dc:description xml:lang="en">Meta-analysis is a statistical technique used to combine the results of several primary studies that have been conducted previously, with the aim of obtaining stronger and more accurate conclusions than can be obtained from each primary study individually. In this case, meta-analysis is performed to evaluate the relationship between obesity and the risk of diabetes mellitus. The data used in this meta-analysis is binary data, which contains information about the presence or absence of diabetes mellitus in individuals who are obese. The odds ratio is used as a measure of effect, which is the ratio between the likelihood of diabetes mellitus in individuals who are obese compared to individuals who are not obese. The results of the meta-analysis show heterogeneity between the primary studies conducted. Therefore, random effects are used in the meta-analysis model. The results of the analysis show that there is a significant relationship between obesity and the risk of diabetes mellitus, with a high odds ratio value. The conclusion from this meta-analysis is that obesity significantly increases the risk of diabetes mellitus. This finding has important implications in efforts to prevent and treat diabetes mellitus, especially in individuals at high risk for obesity.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Faculty of Science and Technology Universitas Jambi</dc:publisher>
	<dc:date>2024-04-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://online-journal.unja.ac.id/msa/article/view/28287</dc:identifier>
	<dc:identifier>10.22437/msa.v4i2.28287</dc:identifier>
	<dc:source xml:lang="en">Mathematical Sciences and Applications Journal; Vol. 4 No. 2 (2024): Mathematical Sciences and Applications Journal; 83-91</dc:source>
	<dc:source>2988-6481</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://online-journal.unja.ac.id/msa/article/view/28287/18245</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2024 Mathematical Sciences and Applications Journal</dc:rights>
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