Although Diabetes is a metabolic disease that cause high blood sugar to mostly people of age 45 years and above whose body either doesn’t make enough insulin or can’t effectively use the insulin it does make. This research use Binary Logistic regression model to analyze predictors for risk factors of Diabetes in Kebbi state as well as build a suitable Binary Logistic regression model capable of finding the relationship among predictors of Diabetes and check which of the predictors are more suitable in predicting of Diabetes. The data used in this study were obtained as secondary data from Federal Medical Centre Birnin Kebbi and Sir Yahaya Memorial Hospital Birnin Kebbi, the data consist 500 people diagnosed for Diabetes out of which some happens to be diabetic positive while others are negative. The analysis was performed using statistical package for social sciences (SPSS Version 21) and it was discovered that; Ages, History of Diabetes, History of HBP/Hypertension, and Overweight/Obese are risk factors of Diabetes and Sex, Frequent urination/increase thirst and Fatigue or Muscle Pain were not risk factors of Diabetes as the model obtained was Logit (P(y=1))=-6.154 + 2.609Age + 2.457History of HBP/Hypertension + 1.307History of Diabetes + 1.237Overweight/Obese.
| Published in | International Journal of Statistical Distributions and Applications (Volume 7, Issue 4) |
| DOI | 10.11648/j.ijsd.20210704.12 |
| Page(s) | 89-94 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
HBP, Diabetes, Logit, Predictors, Binary
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APA Style
Usman Aliyu, Abubakar Umar Bashar, Umar Usman. (2021). Predictors for Risk Factors of Diabetes: Binary Logistic Regression Model Approach. International Journal of Statistical Distributions and Applications, 7(4), 89-94. https://doi.org/10.11648/j.ijsd.20210704.12
ACS Style
Usman Aliyu; Abubakar Umar Bashar; Umar Usman. Predictors for Risk Factors of Diabetes: Binary Logistic Regression Model Approach. Int. J. Stat. Distrib. Appl. 2021, 7(4), 89-94. doi: 10.11648/j.ijsd.20210704.12
AMA Style
Usman Aliyu, Abubakar Umar Bashar, Umar Usman. Predictors for Risk Factors of Diabetes: Binary Logistic Regression Model Approach. Int J Stat Distrib Appl. 2021;7(4):89-94. doi: 10.11648/j.ijsd.20210704.12
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Download@article{10.11648/j.ijsd.20210704.12,
author = {Usman Aliyu and Abubakar Umar Bashar and Umar Usman},
title = {Predictors for Risk Factors of Diabetes: Binary Logistic Regression Model Approach},
journal = {International Journal of Statistical Distributions and Applications},
volume = {7},
number = {4},
pages = {89-94},
doi = {10.11648/j.ijsd.20210704.12},
url = {https://doi.org/10.11648/j.ijsd.20210704.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsd.20210704.12},
abstract = {Although Diabetes is a metabolic disease that cause high blood sugar to mostly people of age 45 years and above whose body either doesn’t make enough insulin or can’t effectively use the insulin it does make. This research use Binary Logistic regression model to analyze predictors for risk factors of Diabetes in Kebbi state as well as build a suitable Binary Logistic regression model capable of finding the relationship among predictors of Diabetes and check which of the predictors are more suitable in predicting of Diabetes. The data used in this study were obtained as secondary data from Federal Medical Centre Birnin Kebbi and Sir Yahaya Memorial Hospital Birnin Kebbi, the data consist 500 people diagnosed for Diabetes out of which some happens to be diabetic positive while others are negative. The analysis was performed using statistical package for social sciences (SPSS Version 21) and it was discovered that; Ages, History of Diabetes, History of HBP/Hypertension, and Overweight/Obese are risk factors of Diabetes and Sex, Frequent urination/increase thirst and Fatigue or Muscle Pain were not risk factors of Diabetes as the model obtained was Logit (P(y=1))=-6.154 + 2.609Age + 2.457History of HBP/Hypertension + 1.307History of Diabetes + 1.237Overweight/Obese.},
year = {2021}
}
TY - JOUR T1 - Predictors for Risk Factors of Diabetes: Binary Logistic Regression Model Approach AU - Usman Aliyu AU - Abubakar Umar Bashar AU - Umar Usman Y1 - 2021/11/10 PY - 2021 N1 - https://doi.org/10.11648/j.ijsd.20210704.12 DO - 10.11648/j.ijsd.20210704.12 T2 - International Journal of Statistical Distributions and Applications JF - International Journal of Statistical Distributions and Applications JO - International Journal of Statistical Distributions and Applications SP - 89 EP - 94 PB - Science Publishing Group SN - 2472-3509 UR - https://doi.org/10.11648/j.ijsd.20210704.12 AB - Although Diabetes is a metabolic disease that cause high blood sugar to mostly people of age 45 years and above whose body either doesn’t make enough insulin or can’t effectively use the insulin it does make. This research use Binary Logistic regression model to analyze predictors for risk factors of Diabetes in Kebbi state as well as build a suitable Binary Logistic regression model capable of finding the relationship among predictors of Diabetes and check which of the predictors are more suitable in predicting of Diabetes. The data used in this study were obtained as secondary data from Federal Medical Centre Birnin Kebbi and Sir Yahaya Memorial Hospital Birnin Kebbi, the data consist 500 people diagnosed for Diabetes out of which some happens to be diabetic positive while others are negative. The analysis was performed using statistical package for social sciences (SPSS Version 21) and it was discovered that; Ages, History of Diabetes, History of HBP/Hypertension, and Overweight/Obese are risk factors of Diabetes and Sex, Frequent urination/increase thirst and Fatigue or Muscle Pain were not risk factors of Diabetes as the model obtained was Logit (P(y=1))=-6.154 + 2.609Age + 2.457History of HBP/Hypertension + 1.307History of Diabetes + 1.237Overweight/Obese. VL - 7 IS - 4 ER -
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