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A Comparison of Decision Tree Induction with Binary Logistic Regression for the Prediction of the Risk of Cardiovascular Diseases in Adult Men
Volume 29, Issue 4 (2018), pp. 675–692
Pub. online: 1 January 2018      Type: Research Article      Open accessOpen Access
Received
1 June 2017
Accepted
1 July 2018
Published
1 January 2018

Abstract

The main purpose of this article was to compare traditional binary logistic regression analysis with decision tree analysis for the evaluation of the risk of cardiovascular diseases in adult men living in the city. Patients and methods. In our study, we used data from the Multifactorial Ischemic Heart Disease Prevention Study (MIHDPS). In the MIHDPS study, a random sample of male inhabitants of Kaunas city (Lithuania) aged 40–59 years was examined between 1977 and 1980. We analysed a sample of 5626 men. Taking blood pressure lowering medicine, disability, intermittent claudication, regular smoking, a higher value of the body mass index, systolic blood pressure, age, total serum cholesterol, and walking in winter were associated with a higher probability of ischemic heart disease or cardiovascular diseases. Having more siblings and drinking alcohol were associated with a lower probability of these diseases. The binary logistic regression method showed a very slightly lower level of errors than the decision tree did (the difference between the two methods was 2.04% for ischemic heart disease (IHD) and 2.86% for cardiovascular disease (CVD), but for consumers, the decision tree is easier to understand and interpret the results. Both of these methods are appropriate to analyse cardiovascular disease data.

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Biographies

Grabauskytė Ingrida
ingrida.grabauskyte@lsmuni.lt

I. Grabauskytė is a PhD student at the Department of Population Studies, Institute of Cardiology, Lithuanian University of Health Sciences. She is a lecturer of biostatistics at the university. Her current research focus is on statistics and medical data analysis.

Tamošiūnas Abdonas
abdonas.tamosiunas@lsmuni.lt

A. Tamošiūnas, Prof. Dr. Habil., head of laboratory, head researcher in the Department of Population Studies, Institute of Cardiology, Lithuanian University of Health Sciences. The field of research – epidemiology and primary prevention of cardiovascular disease.

Kavaliauskas Mindaugas
m.kavaliauskas@ktu.lt

M. Kavaliauskas, Dr. is a lecturer at Kaunas University of Technology. He is giving lectures on mathematical statistics, time series analysis and data mining. His field of scientific research is methods of multivariate data analysis.

Radišauskas Ričardas
ricardas.radisauskas@lsmuni.lt

R. Radišauskas, Prof. Dr., senior researcher in the Department of Population Studies, Institute of Cardiology, Lithuanian University of Health Sciences. The field of research – epidemiology and primary prevention of cardiovascular disease.

Bernotienė Gailutė
gailute.bernotiene@lsmuni.lt

G. Bernotienė, Assoc. Prof. Dr., senior researcher in the Department of Population Studies, Institute of Cardiology, Lithuanian University of Health Sciences. The field of research – epidemiology and primary prevention of cardiovascular disease.

Janilionis Vytautas
vytautas.janilionis@ktu.lt

V. Janilionis is an associate professor at the Department of Applied Mathematics, Kaunas University of Technology. He received a PhD degree (Technical cybernetics and information theory) in 1989 from the Kaunas Polytechnic Institute, Lithuania. His major research interests include statistical data analysis, system modelling, identification and control, data mining methods and applications.


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Open access article under the CC BY license.

Keywords
logistic regression decision tree ischemic heart disease cardiovascular disease

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