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Identification of high-risk group for obesity in the elderly: Decision tree analysis
Journal of the Korean Data & Information Science Society 2022;33:629-43
Published online July 31, 2022;  https://doi.org/10.7465/jkdi.2022.33.4.629
© 2022 Korean Data and Information Science Society.

Myeung Hee Han1

1Department of Nursing, DongYang University
Correspondence to: 1 Professor, Department of Nursing, Dongyang University, Yeongju 36040, Korea. E-mail: dewdrop54@daum.net
Received April 17, 2022; Revised July 6, 2022; Accepted July 11, 2022.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This study attempted to identify the priorities of factors predicting the high-risk group for obesity in the elderly by using decision tree analysis. This was found to be the most likely to be overweight/obese in the entire population over 65 years of age if there was no problem with chewing food, drinking intermittently or daily, and subjects with 3 or more chronic diseases (75.4%). In this study, 100% of men those wo had difficulties in shopping/food making/meal management, attending a club, and not satisfied with their health status was predicted that they were overweight/obese. Women showed ADL is dependent, and those who are emotionally abused while living in the province were most likely to be in the non-overweight/obese group (72.7%). Since this study identified the factors that should be approached first when developing a customized weight control management program for the elderly.
Keywords : Decision tree, elderly aged, obesity.