Babiker Sawsan, Eltayeb Yousif, Sayed-Ahmed Neveen, Abdelhafeez Sitalnesa, Shazly Abdul Khalik El, AlDien M Saif, Nasir Omaima
Department of Mathematics, Turabah University College, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.
Department of Mathematics & Physics, Faculty of Education, Gezira University, P.O. Box 20, Madani, Sudan.
Saudi J Biol Sci. 2021 Dec;28(12):7027-7036. doi: 10.1016/j.sjbs.2021.07.089. Epub 2021 Aug 4.
Analysis through logistic regression explored to investigate the relationship between binary or multivariable ordinal response probability and in one or more explanatory variables. The main objectives of this study to investigate advanced prediction risk factor of Coronary Heart Disease (CHD) using a logit model. Attempts made to reduce risk factors, increase public or professional awareness. Logit model used to evaluate the probability of a person develop CHD, considering any factors such as age, gender, high low-density lipoprotein (LDL) cholesterol, low high-density lipoprotein (HDL) cholesterol, high blood pressure, family history of CHD younger than 45, diabetes, smoking, being post-menopausal for women and being older than 45 for men. Logit concept of brief statistics described with slight modification to estimate the parameters testing for the significance of the coefficients, confidence interval fits the simple, multiple logit models. Besides, interpretation of the fitted logit regression model introduced. Variables showing best results within the scientific context, good explanation data assessed to fit an estimated logit model containing chosen variables, this present experiment used the statistical inference procedure; chi-square distribution, likelihood ratio, Score, or Wald test and goodness-of-fit. Health promotion started with increased public or professional awareness improved for early detection of CHD, to reduce the risk of mortality, aimed to be Saudi vision by 2030.
通过逻辑回归分析来探究二元或多变量有序反应概率与一个或多个解释变量之间的关系。本研究的主要目的是使用逻辑模型调查冠心病（CHD）的高级预测风险因素。尝试降低风险因素，提高公众或专业人士的意识。逻辑模型用于评估一个人患冠心病的概率，考虑诸如年龄、性别、高低密度脂蛋白（LDL）胆固醇、低高密度脂蛋白（HDL）胆固醇、高血压、45岁以下冠心病家族史、糖尿病、吸烟、女性绝经后以及男性45岁以上等任何因素。对逻辑概念进行了简要统计描述，并稍作修改以估计系数显著性检验的参数，置信区间适用于简单、多元逻辑模型。此外，还介绍了拟合逻辑回归模型的解释。在科学背景下显示出最佳结果的变量，对评估拟合包含所选变量的估计逻辑模型的良好解释数据，本实验使用了统计推断程序；卡方分布、似然比、得分或 Wald 检验以及拟合优度。健康促进始于提高公众或专业人士的意识，以改善冠心病的早期检测，降低死亡风险，目标是到 2030 年实现沙特愿景。
