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

Authors

  • Panji Jiblathar Departemen Statistika, Fakultas Sains dan Analitika Data, Institut Teknologi Sepuluh Nopember, Surabaya, 60115
  • Ellys Agustina Program Studi Magister Aktuaria, Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Bandung, Bandung, 40132

DOI:

https://doi.org/10.22437/msa.v4i2.28287

Keywords:

Effect size, Random effect, Obesity, Diabetes mellitus

Abstract

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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Published

2024-04-30

How to Cite

Jiblathar, P., & Agustina, E. (2024). Analisis Meta Hubungan antara Obesitas dan Risiko Diabetes Mellitus dengan Data Binary dan Odd Ratio menggunakan Model Random Effect. Mathematical Sciences and Applications Journal, 4(2), 83-91. https://doi.org/10.22437/msa.v4i2.28287